Customizing speech synthesis

Tailor your assistant's speech to echo your brand's unique tone and personality. With a suite of customization tools, you can fine-tune pitch, speed, accents, and even add a sprinkle of emotion.​

Let´s start with it

Craft compelling texts for your digital voice assistant. Insert your message into the Speech text window in the Message node.

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Text in the Speech window will be used as input for speech synthesis. Customize your text with SSML for even better results.

For top-notch voice synthesis, we've got some copywriting secrets up our sleeve! Check out our tips and tricks on crafting texts that convert beautifully into speech.

Speech synthesis markup language (SSML)

SSML stands for Speech Synthesis Markup Language, and it is an XML-based markup language used to control the synthesis of text-to-speech output. SSML provides a way to specify the pronunciation, intonation, and other aspects of the synthesized speech, giving developers fine-grained control over how the text is spoken.

Some examples of what can be controlled with SSML include:

  • Voice selection: You can choose from a variety of pre-defined voices, including different genders, accents, and languages, or even specify a custom voice using SSML. SSML is used in a variety of applications, such as voice assistants, text-to-speech software, and automated voice response systems, to provide a more natural and user-friendly experience for users.

  • Pronunciation: You can specify the pronunciation of a word or phrase, including how individual phonemes should be pronounced.

  • Prosody: You can control the pitch, volume, and rate of the speech, as well as insert pauses, emphasis, and other effects to give the synthesized speech a more natural-sounding intonation and rhythm.

SSML tags

In the context of SSML, tags are elements of XML markup language that are used to provide instructions for controlling the synthesis of text-to-speech output. These tags are enclosed within angle brackets (< and >), and are used to define specific elements or attributes that are recognized by SSML processors.

Generally, there are two types of tags:

Pair tags, also known as start tags and end tags, consist of two tags that surround a block of content. The first tag is the start tag, and it begins with the name of the element enclosed in angle brackets (< and >). The second tag is the end tag, which begins with a forward slash (/) followed by the name of the element enclosed in angle brackets.

Pair tags define an element that has a beginning and an end, and the content between the tags is considered to be the value of the element.

<prosody> - start tag </prosody> - end tag

<prosody> ... </prosody>

This sentences in not affected by SSML. <prosody> This sentence is modulated with prosody. </prosody> This sentence is no more affected by SSML, as second sentence was enclosed with end tag.
Additional information

Tags can also include attributes, which provide additional information about the element they modify. For example, the <prosody> tag can include the pitch, rate, and volume attributes to control various aspects of the speech.

  • <prosody pitch="+10%" rate="90%"> This sentence will be spoken with a higher pitch (+ 10 %) and slower rate (-10 % or 90 % of default </prosody>

  • The following text will be spoken as individual digits: <say-as interpret-as="digits">1234</say-as>

  • The following sentence will be spoken with a two-second pause in the middle: Hello, <break time="2s"/>world!

Taking the closer look

Delve into the Essential SSML Tags: Enhancing Your Assistant's Voice with Tag Mastery

<break> allows you to insert a pause in the speech. The time attribute specifies the duration of the pause, and the strength attribute specifies the strength of the pause.

Tags usage

SSML code is written in XML format and is typically embedded within the text of the document that is being processed by a text-to-speech system. Here's an example of what SSML code might look like:

Hey there' <prosody rate ="slow">I'm your friendly virtual assistant. </prosody> <break time="500ms/><prosody volume="loud"> How can I help you today?</prosody>

To use SSML-enriched text as output in your digital assistant, copy it in the Speech window in MSG_NODE in the Flow editor.

Tips and trick

Copywriting for your digital assistant should be simple and straightforward to make it easy for users to understand. It is essential to use clear and understandable questions that help the customer formulate their answers. If possible, it is helpful to use the same natural language and words, phrasing, and lexicon that are commonly used in everyday life. This will make it easier to communicate with the voicebot.

Keynotes:

Copywriting structure

Sentence structure

The two basic components of a sentence are topic (téma) and comment (rhéma). The topic is the word or group of words that determine what the sentence is about, while the rheme is part of the sentence that follows and completes the topic. For example, in the sentence "My dog's name is Max", the topic is "My dog" and the rheme is "is named Max". Topic and rheme are important for proper sentence construction and are essential for understanding meaning.

The flexibility in word order is a distinctive feature of Slavic languages, particularly Czech and Slovak, due to their rich inflectional systems.

Order of words is important in SK, CZ language

Changing the word order in a sentence can affect what information we consider important:

CZ:
Petr přišel pozdě do školy. 
     # Important = exactly where (to school, not to date) 
Petr do školy přišel pozdě. 
     # Important = exactly when (late, not on time)
Do školy přišel pozdě Petr. 
     # Important = exactly who (Petr, not Pavel)

Changing the word order can therefore affect which information is emphasised.

CZ:
Klient si může zvolit, zda chce spořit na účtu nebo investovat do podílových fondů. 
Zda chce spořit na účtu nebo investovat do podílových fondů, si může klient zvolit. 

Prosím, pečlivě si pročtěte obchodní podmínky. 
Obchodní podmínky si prosím pročtěte pečlivě. 

Pravděpodobně jste se stali terčem podvodníka. Ihned musíme zablokovat platební kartu. 
Pravděpodobně jste se stali terčem podvodníka. Platební kartu musíme zablokovat ihned.`


---------

SK:
Klient si môže zvoliť, či chce sporiť na účte alebo investovať do podielových fondov. 
Či chce sporiť na účte alebo investovať do podilových fondov, si klient môže sám zvoliť. 

Prosím, pozorne si prečítajte podmienky. 
Obchodné podmienky si prosím prečítajte pozorne. 
 
Pravdepodobne ste sa stali terčom podvodníka. Musíme okamžite zablokovať vašu kreditnú kartu. 
Pravdepodobne ste sa stali terčom podvodníka. Musíme vašu kreditnú kartu zablokovať okamžite.

In English, German, or other languages word order is usually set, but that does mean that we cannot use this principle to our advantage as well. In English, this principle is reversed, the more important information is put in front:

English comparission with SK, CZ language on examples

I saw a lion at the zoo yesterday.          # Important = it was a lion
Yesterday, I saw a lion at the zoo.         # Important = it was yesterday


I can only play the piano.   # Of all instruments, I play only piano (not guitar, not flute)
I only can play the piano.   # Playing piano is my only skill (not dancing, not singing)
CZ:
Novou kartu vám můžeme poslat poštou, případně kurýrem. Také si ji můžete vyzvednout na pobočce. Kterou variantu preferujete?”`
SK:
“Novú kartu vám môžeme poslať poštou alebo kuriérom. Môžete si ju tiež vyzdvihnúť na pobočke. Ktorú možnosť uprednostňujete?”
EN:
"We can send you a new card by post or courier. You can also pick it up at a branch. Which option of these two options do you prefer?"

You can also use sentences that require a multiple-choice answer, such as "Which of the options do you wish to choose: A or B?". Alternatively, we recommend accompanying both options with a verb so that each option is its own sentence and it is clear that these are choices, for example, "Do you want A or do you need B? Another strategy is to first inform the customer of the options and then ask them to choose.

CZ:
Vyberte si, zda se chcete přihlásit pomocí e-mailu, nebo pomocí Facebooku.
Řekněte mi, zda chcete zaslat fakturu na e-mail, nebo zda ji máme poslat poštou.
Potřebuji nejdřív vědět, zda již u nás máte účet, nebo ho teprve chcete založit. 

SK:
Vyberte si, či sa chcete prihlásiť cez e-mail alebo pomocou Facebooku”
“Povedzte mi, či chcete faktúru poslať e-mailom alebo či ju máme poslať poštou”,
“Najprv potrebujem vedieť, či už u nás máte účet, alebo si ho práve chcete otvoriť.”. 

EN:
"Choose whether you want to sign in via email or Facebook"
"Tell me if you want us to send you an invoice via email or whether you prefer to receive it as a paper letter"
"First, I need to know if you already have an account with us or if you just want to open one".

However, the number of unwanted answers can be reduced by appropriate copywriting with more distinctive intonation (see intonation) and emphasis on the individual options. One way to write a question that requires multiple choice is to use clear and specific terms that clearly identify each option. For example, instead of asking "Do you want A or B?" you can try something along the lines of:

In spoken language, however, this difference in meaning is unclear in both languages as well as several others (English, German, French etc.), and it happens that customers do not understand the question at the first attempt and answer yes/no instead of choosing from the options. It is therefore necessary to take this into account when designing the conversation and prepare the scenario for such situations.

In Slovak, a similar rule does not apply for or, the writing of commas is governed by different rules.

Example 1.
Yes/no question. We're asking if they're interested in a drink at all. The expected answer is yes/no.

Do you want (A or B)? 
Dáš si kávu nebo čaj?
Do you want (coffee or tea)?
Example 2.
We'll serve you either coffee or tea. Choose one of the two. We expect a response of "coffee, please" or "tea with honey, thanks".

Do you want A, or B? 
Dáš si kávu, nebo čaj?
Do you want (coffee) or do you want (tea)?

In Czech, we distinguish grammatically by a comma between two mutually exclusive choices. In this case, the comma is meaning-forming.

Multiple choice question

CZ: 
Voláte kvůli své objednávce, případně dříve zakoupeného výrobku? Stačí mi jednoduchá odpověď ano nebo ne.
Zboží můžete vrátit na prodejně, kurýrem nebo přes zásilkovnu. Kterou z těchto možností zvolíte?

EN:
Are you calling to unblock your account? Please answer with yes or no.

TIP! In the beginning, before customers get used to the new technology, it is a good idea to provide short instructions on how to interact with the voicebot to avoid confusion and the tendency to press buttons like with IVR.

Wrong practice examples:

  • We don't want to make the user talk over the digital assistant! On the contrary, we want the user's answer to be as concise and clear as possible, and thus easily and reliably recognizable by the voicebot. It is therefore a good idea to make sure that each chatbot text contains only one clear and understandable question.

  • Having two questions in one text also makes it difficult to adjust the synthesis, as the question mark is naturally followed by a longer pause before the start of the next sentence, which is not correctable by the SSML breaktime tag. From the user's perspective, it looks as if the voicebot has already finished, the user starts to answer and jumps in to talk over the robot.

  • It is important to make sure that one voicebot's message does not contain two questions at the same time, as this can cause confusion and complicate understanding between the bot and the user. When multiple questions are included in the output message, it can confuse the user. They may not know which question to focus on or what the correct answer is. This can cause the user to feel frustrated which can reduce communication effectiveness and make the user experience less enjoyable.

Multiple questions in a single message

  • If you ask the question at the end of the speech, the customer has already heard all the relevant information and is ready to respond.

  • In general, people are more likely to retain the freshest information in their memory, i.e. the information they heard last (see theme).

  • This will increase the likelihood that the customer will respond concisely and appropriately, and the voicebot will recognize everything correctly and provide the most complete answer to the customer's query.

  • The question asked will indicate to the customer that it is time for him to start talking.

Supporting argument for positioning question at the end of the speech:

CZ:
Chtěl bych vám nabídnout konzultaci s naším expertem. Ozve se Vám a zdarma Vám provede kalkulaci toho nejvýhodnějšího pojištění. Máte zájem? 

Rádi bychom Vám poskytli konzultaci zdarma. Ozve se Vám náš expert s kalkulací, které pojištění by pro Vás bylo nejvhodnější. Souhlasíte?

Rather, the solution is built on alternating between periods when the voicebot is speaking and not listening (running text-to-speech synthesis) and when the voicebot is silent, listening and evaluating the transcript of the response (running speech-to-text transcription). If the customer speaks without the voicebot finishing speaking, speech-to-speech transcription does not run and part of the response is lost, which can lead to misrecognition of intent.

It's better if the text of the voicebot contains the question at the end of the speech. This will help to prevent the customer from jumping into the voicebot's speech. The solution is not designed to allow the customer to interrupt the virtual assistant, while the voicebot is able to go back and finish the rest of its speech.

Remember that achieving natural and expressive intonation in TTS systems can be challenging, as it requires capturing the nuances of human speech. It may take some experimentation and refinement to achieve the desired results.

Position of the question in digital assistant's message

CZ:
Zkusíme to znovu? 
Vyplnil jste všechny údaje správně?
Přejete si reklamaci řešit raději písemnou cestou?

A question should never be phrased negatively. This is because people are generally more willing to accept positive information and ideas than vice versa. Phrasing the question negatively can reduce the likelihood that the voicebot will correctly understand the customer's answer.

CZ:
Nechcete to zkusit znovu?      
Neudělali jste chybu? 
Jste si jistý, že jste neudělal chybu?
Nepřejete si reklamaci raději řešit písemnou cestou? 

SK:
Nechcete to skúsiť znova?   
Neurobili ste chybu?  
Nechceli by ste svoju sťažnosť riešiť radšej písomne?

EN:
Won't you try again?
Don't you want to deal with reclamation via e-mail?

What would answer yes (ano/áno) mean in this case? Yes, I want or Yes, I indeed don't want to? This situational context cannot be discerned with 100% confidence, so we recommend phrasing questions positively or neutrally.

Question wording is a key element of the voicebot scenario. The wording of the question influences the phrasing of customer's answer, and therefore the intent that must be trained for the virtual assistant to recognize the answer.

Question formulation

Based on the length of the sentence sometimes the quality of the synthesis can be quite fluctuating, appearing artificial and not very natural. In such cases, it is useful to shorten the copywriting or add or edit some words to the text to make the voice synthesis sound better. This approach can help create a more natural and beautiful voice synthesis without the need for complicated settings or SSML tags.

10 Copywriting tips for your digital assistant with speech synthesis

  1. The copywriting must be snappy, clear, and understandable.

  2. Speak the language of your customers. Use terms and slang they understand.

  3. Never phrase questions negatively.

  4. 1 message node = 1 question maximum.

  5. The ideal placement of the question is at the end of the message.

  6. Never ask two different things with one question.

  7. For multiple-choice questions, make sure to clearly differentiate the options. If appropriate, rephrase to an announcement sentence and inform the customer that they have to choose and list options.

  8. Spelling and grammatical correctness in Speech is secondary. However, make errors consciously so that they benefit the quality of the synthesis.

  9. Avoid foreign language expressions whenever possible. Alternatively, we write them in such a way that they can be read alphabetically

  10. Special characters and cases that are to be read aloud are broken down with words.

Intonation best practice

Master the art of customizing speech synthesis intonation with SSML on our dedicated documentation page. Learn to personalize your AI voice with precision and creativity for a truly tailored and engaging auditory experience!

Here are some basic tips

  1. Understand the context: Intonation conveys meaning and emotion in speech. It's important to consider the context and intended message of the text. Identify the keywords, phrases, or sentences that require specific intonation patterns to convey the desired emphasis or emotion.

  2. Use punctuation: Punctuation marks such as commas, periods, question marks, and exclamation marks indicate natural breaks and changes in intonation. Make sure to add appropriate punctuation to your text to guide the TTS system's intonation.

  3. Prosody tags: Utilize SSML tags to explicitly specify the desired intonation patterns for specific words or phrases.

  4. Experiment with pitch and duration: Intonation involves variations in pitch and duration. Adjusting the pitch can create rising or falling intonation patterns while manipulating the duration of syllables or phrases can add emphasis or rhythmic patterns. Experiment with these parameters to achieve the desired intonation.

  5. Listen and iterate: After applying intonation modifications, listen to the generated speech and evaluate the effectiveness of the intonation patterns. Make adjustments as needed to achieve the desired expressive quality and convey the intended meaning.

  6. Consult native speakers: If possible, seek feedback from native speakers of the target language to ensure that the intonation sounds natural and appropriate. Native speakers can provide valuable insights and guidance on the intonation patterns specific to the language and context.

Remember that achieving natural and expressive intonation in TTS systems can be challenging, as it requires capturing the nuances of human speech. It may take some experimentation and refinement to achieve the desired results.

Intonation curve

Text-to-speech synthesis is also able to automatically detect the sentence type and set the corresponding intonation curve. This means that you can easily create a synthesized voice that sounds natural and matches the text you enter accurately.

In Azure Audio Content Creator, you can adjust intonation in sections, which means you can set intonation for each sub-section, phrase, or word separately, instead of having to set intonation for the whole sentence. This allows you to capture different intonation nuances more accurately and gives you more control over how the neural voice will appear.

Accentuating intonation allows listeners to distinguish between the different ideas and information contained in a sentence. By adjusting intonation curves, you can highlight important points or emphasize changes in mood or emotion, which will help the listener better understand and remember what the voice is saying.

Intonation best practice tips

Here's how you can work with the Intonation curve effectively:

  • Understand the Intonation curve: The Intonation curve represents the pitch contour of the speech waveform. It visualizes the changes in pitch over time. The x-axis represents time, and the y-axis represents pitch.

  • Identify key points: Identify the key points in the text where you want to manipulate the intonation. These points could include emphasized words, important phrases, or sections that require specific intonation patterns.

  • Add anchor points: Add anchor points on the Intonation curve to indicate the pitch changes. Click on the curve at specific time points to create anchor points. These points will serve as the reference for manipulating the pitch.

  • Adjust pitch and duration: Drag the anchor points up or down to adjust the pitch at those time points. Moving them upward raises the pitch while moving them downward lowers the pitch. You can also drag the edges of the anchor points to modify the duration of the pitch change.

  • Create prosody patterns: By adding multiple anchor points and adjusting their positions, you can create inflection patterns such as rising, falling, or fluctuating intonation. For example, a rising intonation pattern can indicate a question, while a falling intonation pattern can denote a statement or completion.

  • Preview and refine: Preview the speech with the modified Intonation curve to evaluate the impact of your changes. Fine-tune the positions of anchor points as needed to achieve the desired intonation patterns.

  • Iterate and experiment: Intonation patterns can be subjective and depend on the context and language. Experiment with different anchor point positions, shapes, and durations to find the most appropriate intonation for your specific text.

When adjusting intonation curves, you should consider several factors such as sentence length, rhythm, accent, and the emphasis you want to convey. It is important to remember that intonation is a complex subject and that you need to practice and try different approaches.

Melody patterns

Here are some examples of inflexion patterns you can achieve:

To create a rising intonation pattern, you would place anchor points at the beginning of a phrase or sentence and gradually raise the pitch as you move forward in time. This pattern is commonly associated with questions or uncertainty.

Pauses and breaks best practice

Basics

The <break> tag is used to create a pause of a given length in the text. This tag can be used, for example, to express a pause between words or sentences, which can help to improve the naturalness of the delivery.

Azure Audio content creator tool offers both predefined tags and the ability to incorporate breaks of a length of our choosing.

The <break> tag in SSML is used to insert a pause or a break in the speech output. It allows you to specify the duration and the strength of the pause. The <break> tag can be used with the following attributes:

time: Specifies the duration of the pause in seconds or milliseconds. For example, <break time="500ms"/> inserts a pause of 500 milliseconds.

strength: Specifies the strength or intensity of the pause. It can have values like "none", "x-weak", "weak", "medium", "strong", or "x-strong". The actual interpretation of these values may depend on the specific text-to-speech engine used.

Example

  • Hello, <break time="500ms"/> how are you today?

  • Hello, <break strenght="medium"/> how are you today?

Pronunciation best practice

Phoneme-defined pronunciation

Stress can have a huge impact on pronunciation.

When a word is stressed, the stressed syllable is typically pronounced with greater intensity, higher pitch, and longer duration compared to unstressed syllables. Additionally, the quality of vowels in stressed syllables may also be affected, with stressed vowels often being pronounced with more clarity and fullness.

To provide some examples in IPA (International Phonetic Alphabet), let's consider a few Czech words:

"kniha" (book): /ˈkɲɪɦa/ The primary stress falls on the first syllable (/kɲ/), making it more prominent in pronunciation.

"univerzita" (university): /ˌunɪvɛrˈzɪta/ The primary stress is on the second syllable (/ɪv/), while the first syllable (/u/) carries secondary stress. The following syllables (/ɛrˈzɪt/ and /ta/) are unstressed.

"překvapení" (surprise): /ˌpr̝̊ɛkvaˈpɛɲi/ The primary stress is on the second syllable (/ɛkva/), and the first syllable (/pr̝̊/) carries secondary stress. The final syllable (/ɲi/) is unstressed.

These examples illustrate the general stress patterns in Czech, where the stressed syllables are emphasized in terms of intensity, pitch, duration, and sometimes vowel quality. It's important to consult native speakers or audio resources to further refine your pronunciation and understand the intricacies of Czech stress patterns.

Foreign words pronunciation

When using Azure's Speech Studio with neural voices to handle foreign word pronunciation, here are some tips to ensure accurate pronunciation:

  • Phonetic spelling: Provide a phonetic spelling of the foreign words using the International Phonetic Alphabet (IPA) or a transcription system familiar to the base language neural voices. This helps the TTS system understand the correct pronunciation of the word.

  • Lexicon customization: Utilize the lexicon customization feature in Azure's Speech Studio to add pronunciation rules for specific foreign words. This allows you to specify the pronunciation of each word or phrase more precisely.

  • Pronunciation rules: Create pronunciation rules for common patterns found in foreign words. For example, if there is a consistent pattern of stress in the foreign language, you can define rules to apply stress in the appropriate position.

  • Contextual cues: Provide additional context within the text to help guide the TTS system's pronunciation. This could include nearby words or phrases that assist in determining the correct pronunciation of the foreign word.

  • Test and iterate: After applying the above techniques, listen to the generated speech and identify any mispronunciations. Adjust the phonetic spellings, lexicon entries, or pronunciation rules as necessary and continue testing until the desired pronunciation is achieved.

It's important to note that while these tips can improve the accuracy of foreign word pronunciation in TTS systems, the results may still vary. TTS systems are trained on large datasets and generalize pronunciation based on the language's phonetic patterns. Handling foreign words can be challenging due to the diverse pronunciation rules across languages.

Some phrases or individual words from foreign vocabulary are trained in the default text-to-speech model and synthesized is smooth, localized to base language, and pleasant to the ear. Sounds fine without adjustments:

  • Nejpoužívanější vyhledávač v Česku je Seznam, nikoliv Google.

  • Letíme na dovolenou se společností Lufthansa.

  • Koupím ojetý renault.

Other phrases or words can be very similar and comprehensible, with a few tweaks here and there. Even though their pronunciation is nearly correct, this can cause an uncanny valley effect:

  • Ceny maji jako Deutsche bahn, ale služby jako nejposlednější drožka.

deutsche is pronounced correctly like [dɔ͡ɪˈt.ʃɛ.], but bahn sounds like [ba.ɦaːˈ.ẽˈ] and would be needed to be adjusted

  • Potřebuji znát vaši IP adresu.

IP being pronounced like [iːˈ.pɛː], which would be comprehensible, but in the case would be better to adjust English pronunciation to Czech as [a͡j.piː] 🇨🇿Pronunciation of numbers followed by currency signs is quite different from common reading rules.With prices, sums of money, or values, we often omit words describing the decimal order of fractional part ([desetiny, setiny])

Integers

  • If digits have fewer than or exactly 6 digits, they are always read decadically as default, regardless of whether a space separates orders of thousands 1234 1 234 Both numbers are pronounced as: TISÍC DVĚ STĚ TŘICET ČTYŘI 12345 12 345 Both numbers are pronounced as: DVANÁCT TISÍC TŘI STA ČTYŘICET PĚT 123456 123 456 Both numbers are pronounced as: STO DVACET TŘI TISÍC ČTYŘI STA PADESÁT ŠEST

  • If digits have 7 or more characters, they are read decadically only if the order of thousands is separated by a space. Numeric string notation without spaces defaults to reading each digit in turn. 1234567 is pronounced JEDEN DVA TŘI ČTYŘI PĚT ŠEST SEDM 1 234 567 is pronounced MILION DVĚ STĚ TŘICET ČTYŘI TISÍC PĚT SET ŠEDESÁT SEDM 123456789 is pronounced JEDEN DVA TŘI ČTYŘI PĚT ŠEST SEDM OSM DEVĚT 123 456 789 is pronounced STO DVACET TŘI MILIONÚ ČTYŘI STA PADESÁT ŠEST TISÍC SEDM SET OSMDESÁT DEVĚT

  • If we need shorter numbers to be read each digit in turn, there are several ways to do it A. Add spaces in between 1 2 3 4 5 6 is pronounced JEDEN DVA TŘI ČTYŘI PĚT ŠEST B. Add commas in between 1, 2, 3, 4, 5, 6 is pronounced JEDEN DVA TŘI ČTYŘI PĚT ŠEST with more distinct pauses between each of them C. Use SSML alias for spelling (hláskování) <say-as interpret-as="spell" format="undefined">123456</say-as> is pronounced JEDEN DVA TŘI ČTYŘI PĚT ŠEST

  • If we need longer number to be read each digit in turn, copywriting input needs to be adapted accordingly A. Use numeric string without spaces 1234567890 B. Separate each digit with spaces 1 2 3 4 5 6 7 8 9 C. Separate each digit with interpunction 1,2,3,4,5,6,7,8,9 These numbers will be pronounced as JEDEN DVA TŘI ČTYŘI PĚT ŠEST SEDM OSM DEVĚT

Phone numbers

For the pronunciation of telephone numbers:

A. Write them down in iso format including prefix Volejte +420 800 148 148 is pronounced VOLEJTE PLUS ČTYŘI STA DVACET, OSM SET, STO ČTYŘICET OSM, STO ČTYŘICET OSM

B. Separate custom sections with interpunction Volejte 800, 148, 148 is pronounced OSM SET, STO ČTYŘICET OSM, STO ČTYŘICET OSM Volejte 212-456-789 is pronounced DVĚ STĚ DVANÁCT, ČTYŘI STA PADESÁT ŠEST, SEDM SET OSMDESÁT DEVĚT Volejte 800, 54, 12, 12 is pronounced OSM SET, PADESÁT ČTYŘI, DVANÁCT, DVANÁCT Volejte 800, 12, 7, 7, 7. 7 is pronounced OSM SET, DVANÁCT, SEDM, SEDM, SEDM, SEDM

C. Write them down as alphabetical string Volejte osm set dvanáct čtyři sedmničky Volejte osm set dvanáct sedm sedm sedm sedm

D. Separate sections with spaces, as long it's meant to be pronounced in 3-2-2-2 or 3-2-1-1-1-1 800 54 12 12 is pronounced OSM SET, PADESÁT ČTYŘI, DVANÁCT, DVANÁCT 800 54 1 2 1 2 is pronounced OSM SET, PADESÁT ČTYŘI, JEDNA, DVA, JEDNA, DVA

Long numerical strings (IDs, codes)

For pronunciation of long numerical strings (order IDs etc.):

A. Write numerical strings without spaces to be read one digit in turn Objednávka 01304578931 Objednávka NULA JEDNA TŘI NULA ČTYŘI PĚT SEDM OSM DEVĚT TŘI JEDNA

B. Customize pronunciation by breaking it into smaller chunks with interpunction Objednávka 01, 30, 45, 78, 9-3-1 Objednávka NULA JEDNA, TŘICET, ČTYŘICET PĚT, SEDMDESÁT OSM, DEVĚT TŘI JEDNA

Numeric date notation

A. ISO DD-MM-YYY 01-11-1995 1-11-1995 Pronounced as [1. listopadu 1995]

B. ISO YYYY-MM-DD 1995-11-01 1995-11-1 Pronounced as [1. listopadu 1995]

C. ISO DD.MM.YYYY datum 01.11.1995 datum 01. 11. 1995 datum 1.11.1995 datum 1. 11. 1995 Pronounced [as 1. listopadu 1995]

A safe and simple way is to transcribe the date alphanumerically:

datum 1. listopadu 1995 prvního listopadu 1995 Pronounced as [1. listopadu 1995]

prvního jedenáctý 1995 Pronounced as [prvního jedenáctý 1995]

These formats WON'T WORK and will be pronounced incorrectly, even if tagged with SSML alias reading rules for dates

  • DD.MM - 1.11. - [jedna hodina jedenáct minut]

  • DD. MM - 1. 11. - [první jedenáctý]

  • DD/MM - 01/11 - [nula jedna lomítko jedenáct]

  • DD/MM/YYYY - 01/11/1995, 1/11/1995 - [nula jedna lomítko jedenáct lomítko 1995]

  • SSML alias reading rules not supported

To be pronounced correctly, dates containing only date + month must be written manually

prvního listopadu dne 2. listopadu 31. března 17. listopad

Time notation

Standard iso format is supported and is pronounced as time correctly by default

  • HH:mm - 15:52 - [Patnáct hodin padesát dvě minuty]

  • HH:mm:ss - 15:52:25 - [Patnáct hodin padesát dva minut dvacet pět sekund]

  • HH.mm - 15.52 - [Patnáct hodin padesát dva minut]

Whole hours, even if written down digital, are pronounced as analog time

  • HH:00 - 15:00 - [Patnáct hodin]

  • HH:00:00 - 15:00:00 - [Patnáct hodin]

The Czech SI unit system IS NOT SUPPORTED

Won't pronounce hod or h as hodin/hodiny 15 hod - [patnáct hod] 15 h - [patnáct há] Won't pronounce min or mins as minut/minuty 15 min - [patnáct min] 15 hod 15 min - [patnáct hod patnáct min]

In case you need time to be pronounced as analog or Czech SI units to be pronounced correctly, it is necessary to transcribe your input

  • 15 hod → 15 hodin

  • 15 min → 15 minut

  • 2 min → 2 minuty

  • 15:15 → čtvrt na čtyři | čtvrt na čtyři

  • 12:00 → poledne

  • 12:30 → půl jedné odpoledne

Customizing speech synthesis of variables

A variable is a named storage location that holds a value in computer programming. It is a fundamental concept used to store and manipulate data within a program. In the context of voicebots and speech applications, variables can be used to store and retrieve information that is relevant to the conversation or user interaction.

General use

To use variables in the speech output of a voicebot, you need to incorporate the variable values within the text that the voicebot will read out loud (in the Message node, fill in the Speech window).

General approach:

  1. Define and store the variable values: In your voicebot's code or script, define and store the necessary variable values based on user input or other relevant data. For example, you might have a variable named customer_name that stores the user's name.

  2. Construct the speech output text: Craft the message, and include the variable values where appropriate.

  3. Set Speech in Message node: Paste the constructed speech input for the text-to-speech engine to convert it into audible speech. Your digital assistant will then speak the generated text, incorporating the variable values dynamically.

Common problems and FAQ

Why do I cannot use <alias> SSML tags on part of a speech with a variable in it?

Since variable values are dynamic, there's no point in replacing them with a single alias. Synthesized message would always be the same regardless of the variable's value.

Why is it challenging to customize the synthesis intonation of text with variables?

Variable values might significantly vary in length and therefore the rhythm of speech, the number of syllables, vowel content and a prosody of a sentence is a slightly different with every case.


SPEECH input: Jste prosím {gender] {name_surname}?

Possible text-to-speech outputs:
Jste prosím pan Jan Kár?
Jste prosím pan Ivo Krč?
Jste prosím pan Pavel Novák?
Jste prosím paní Eva Černá?
Jste prosím paní Eliška Drahokoupilová?
Jsem prosím Filémína Strčskrzprstová?
Jste prosím pan Květoslav Podhorodecký?
[...]

Only way to handle this situation is to temporarily substitute variables with some dummy values as examples.

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