Implementing Speech-to-Text Solution with Diarization for Multi-Speaker using Azure AI
Question
You are working on implementing a speech-to-text solution that can perform diarization for multi-speaker.
It is also required that speakers in conversation are distinguished along with the time.
Which of the below listed will help us implement this solution?
Answers
Explanations
Click on the arrows to vote for the correct answer
A. B. C. D.Corrcet Answer: C.
Option A is INCORRECT.
Speech SDK helps to develop speech-enabled applications.
However, it is not suited for the transcription in scenarios as detailed in the question.
Option B is INCORRECT.
Speech to text API is an ideal fit when we cannot use Speech SDK.
Below are the important points to be considered while using Speech to text API.
- Only up to 60 seconds of audio could be contained for requests using REST API and transmitting audio directly.
- Partial results are not available when we use speech-to-text API.
Only the final results are available.
Option C is CORRECT.
Conversation Transcription is a speech-to-text solution that provides real-time and asynchronous transcription of conversation.
Conversation Transcription has the below features.
- speech recognition
- speaker identification
- sentence attribution to speaker (also known as diarization) Option D is INCORRECT.
Set of REST API operations, the Batch transcription API, enables transcription of audio stored in storage.
The transcription results could be asynchronously received by simply referring to audio storage by a typical URI or a shared access signature (SAS) URI.
References:
To implement a speech-to-text solution that can perform diarization for multi-speaker and distinguish speakers along with the time, the best option is to use Conversation Transcription.
Conversation Transcription is a feature provided by the Azure Speech Services that enables the transcription of audio conversations in real-time. The Conversation Transcription API can transcribe audio recordings with multiple speakers, and it can also identify each speaker in the conversation and associate each utterance with the corresponding speaker.
The Speech-to-text SDK and API are other features provided by Azure Speech Services that can be used for speech-to-text conversion. However, they are not specifically designed for multi-speaker transcription and do not include diarization capabilities.
Batch Transcription, on the other hand, is a feature that allows you to transcribe audio files in batches. While it is possible to use Batch Transcription to transcribe audio recordings with multiple speakers, it does not provide real-time transcription, and it does not include speaker diarization.
In summary, if you want to implement a speech-to-text solution that can perform diarization for multi-speaker and distinguish speakers along with the time, the best option is to use Conversation Transcription.
