results: A list of all accumulated recognition results. The accumulator tracks results as they are added and maintains several useful instance variables: To help combine multiple responses, the Swift SDK provides a SpeechRecognitionResultsAccumulator object. This is especially common for long audio files, since the entire transcription may contain a significant amount of text.
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Instead, the transcription may be streamed over multiple responses, each with a chunk of the overall results. The Speech to Text service may not always return the entire transcription in a single response. It’s important to specify the correct audio format for recognition requests that use the microphone: // compressed microphone audio uses the opus format let settings = RecognitionSettings ( contentType : "audio/ogg codecs=opus" ) // uncompressed microphone audio uses a 16-bit mono PCM format at 16 kHz let settings = RecognitionSettings ( contentType : "audio/l16 rate=16000 channels=1" ) Recognition Results Accumulator in detail To disable compression, set the compress parameter to false. To reduce latency and bandwidth, the microphone audio is compressed to OggOpus format by default. By watching for the final property, your app can stop the microphone after determining when the user has finished speaking. For example, you could use a button to start/stop transcribing, or you could require users to press-and-hold a button to start/stop transcribing.įinal Result: Each transcription result has a final property that is true when the audio stream is complete or a timeout has occurred. User Interaction: Your app could rely on user input to stop the microphone. There are two different ways that your app can determine when to stop the microphone: The framework internally manages the microphone, starting and stopping it with various method calls ( recognizeMicrophone and stopRecognizeMicrophone, or startMicrophone and stopMicrophone). The Speech to Text framework makes it easy to perform speech recognition with microphone audio. Advanced Usage Microphone Audio and Compression in detail How you call it is up to you, but the above provides a typical example of how you would record while responding to a UI action. The above example uses the recognizeMicrophone method within a function, which can be called from a button click or user input. import SpeechToTextV1 let authenticator = WatsonIAMAuthenticator ( apiKey : "
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The following example shows how to transcribe an audio file using the standard API endpoint. Starscream is a recursive dependency that adds support for WebSockets sessions. IMPORTANT: Please be sure to include both amework and amework in your application. Transcriptions are supported for various audio formats and languages.
It uses machine intelligence to combine information about grammar and language structure to generate an accurate transcription. The IBM Watson Speech to Text service enables you to add speech transcription capabilities to your application.
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