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Audio Format And Voices

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  Configure Audio Format and Voices When generating speech, a SpeechConfig object can be utilized to tailor the audio provided by the Azure AI Speech service. Audio Format The Azure AI Speech service offers various output formats for the audio stream produced by speech synthesis. You can select a format that aligns with your specific requirements: Audio file type Sample-rate Bit-depth The supported formats are indicated in the SDK using the SpeechSynthesisOutputFormat enumeration. Voices The Azure AI Speech service offers a variety of voices that can be utilized to customize your speech-enabled applications. There are two kinds of voice that you can use: Standard voices - synthetic voices created from audio samples. Neural voices - more natural sounding voices created using deep neural networks. Voices are identified by names that indicate a locale and a person's name Use Speech Synthesis Markup Language While the Azure AI Speech SDK enables you to submit plain text to be synthes...

Text To Speech API

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  Use the Text to Speech API The Azure AI Speech service provides additional REST APIs for speech synthesis, much like its Speech to Text APIs: The Text to speech API, which is the primary way to perform speech synthesis. The Batch synthesis API, which is designed to support batch operations that convert large volumes of text to audio, for example to generate an audio-book from the source text. Using the Azure AI Speech SDK Similar to voice recognition, the Azure AI voice SDK is actually used to create the majority of interactive speech-enabled applications. The pattern for implementing speech synthesis is similar to that of speech recognition: Use a SpeechConfig object to encapsulate the information required to connect to your Azure AI Speech resource. Specifically, its location and key. Optionally, use an AudioConfig to define the output device for the speech to be synthesized. By default, this is the default system speaker, but you can also specify an audio file, or by explic...

Azure AI Speech To Text API

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  Use the Azure AI Speech to Text API The Azure AI Speech service supports speech recognition through two REST APIs: The Speech to text API, which is the primary way to perform speech recognition. The Speech to text Short Audio API, which is optimized for short streams of audio (up to 60 seconds). Depending on how long the spoken input is expected to be, you can use either API for interactive voice recognition. Additionally, you can batch transcribe several audio recordings to text using the Speech to Text API. Using the Azure AI Speech SDK There is a standard procedure for utilizing the Speech to Text API, even though the specifics differ based on the SDK being used (Python, C#, etc.) : Use a SpeechConfig object to encapsulate the information required to connect to your Azure AI Speech resource. Specifically, its location and key. Optionally, use an AudioConfig to define the input source for the audio to be transcribed. By default, this is the default system microp...

Create Speech-Enabled Apps With Azure AI Services

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  Introduction You may create speech-enabled apps with the Azure AI Speech service. You can create speech-enabled applications using the APIs provided by Azure AI Speech. This includes: Speech to text - An API that enables speech recognition in which your application can accept spoken input. Text to speech - An API that enables speech synthesis in which your application can provide spoken output. Speech Translation - An API that you can use to translate spoken input into multiple languages. Speaker Recognition - An API that enables your application to recognize individual speakers based on their voice. Intent Recognition - An API that uses conversational language understanding to determine the semantic meaning of spoken input. Provision An Azure Resource For Speech You must first build an Azure AI Speech resource in your Azure subscription in order to use Azure AI Speech. Either a multi-service Azure AI Services resource or a single Azure AI Speech resource are available. Afte...

Custom Translations

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  Define Custom Translations Although Azure AI Translator's default translation model works well for general translation, you might need to create a translation solution for companies or sectors with particular vocabularies of terms that call for specialized translation. To solve this problem, you can create a custom model that maps your own sets of source and target terms for translation. To create a custom model, use the Custom Translator portal to- Create a workspace linked to your Azure AI Translator resource. Create a project. Upload training data files and train a model Test your model and publish your model. Make translation calls to the API. You can use the category parameter in translate calls to your Azure AI Translator resource to specify the unique category Id that your custom model has been assigned. This will cause your custom model to execute translation rather than the default model. How To Call The API ? To initiate a translation, you send a POST request to the fol...

Specify Translation Options

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  The Translate function of the API supports numerous parameters that affect the output. Word Alignment Words in written English (written in Latin script) are separated by spaces. This isn't always the case, though, in several other languages, more especially, scripts. For example, translating "Smart Services" from en (English) to zh (Simplified Chinese) produces the result " 智能服 务 ", and it's difficult to understand the relationship between the characters in the source text and the corresponding characters in the translation. To resolve this problem, you can specify the includeAlignment parameter with a value of true in your call to produce the result. Sentence Length When deciding how best to display a translation in a user interface, for instance, it may be helpful to know the translation's length (i.e., character count). By making the includeSentenceLength argument true, you can obtain this data. Profanity Filtering Profanity can occasionally be foun...

Translate Text With Azure AI Translator Service

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  Introduction You may develop clever apps and services that can translate text between languages with the help of the Translator service. The capacity of speakers of various languages to communicate with one another is frequently a crucial prerequisite for global solutions, and there are numerous widely spoken languages in the globe. An API for translating text between 90 recognized languages is offered by the Azure AI Translator.   Provision An Azure AI Translator Resource Azure AI Translator provides a multilingual text translation API that you can use for: Language detection. One-to-many translation. Script transliteration (converting text from its native script to an alternative script).   Azure Resource For Azure AI Translator You need to allocate a resource in your Azure subscription in order to use the Azure AI Translator service. The Text Analytics API can be used in a multi-service Azure AI Services resource, or you can provision a single-s...