interactive assistant
This code implements a voice-based chatbot using the following components:
1.Audio Recording: Uses the sounddevice library to record audio from the microphone. The recorded audio is processed as a NumPy array.
2.Speech-to-Text (ASR): Employs the Whisper model (base version) to transcribe the recorded audio into text. The transcription process converts the raw audio input into a string of text.
3.Text-to-Response: Utilizes the Mistral API (via MistralClient) to generate a conversational response based on the transcribed text. Messages are sent in a chat-like format to the API, which responds with generated content.
4.Text-to-Speech (TTS): Integrates Azure Cognitive Services for speech synthesis. Converts the text response into speech and plays it back to the user.
5.Asynchronous Workflow: The entire process is managed asynchronously using Python's asyncio, ensuring non-blocking operations for recording, transcription, and generating responses.
6.API Keys and Configuration: Contains API keys for Mistral and Azure Cognitive Services, and specifies the Azure region.
7.Execution:
The main function orchestrates the workflow:
Records audio.
Transcribes the recorded audio into text.
Generates a response based on the text input.
Synthesizes and plays back the response.
8.Error Handling: Includes basic error handling for response generation and speech synthesis to manage exceptions during runtime.
Use Case: This program facilitates an interactive voice chatbot that listens to the user, processes the input, generates a contextually relevant reply, and delivers the reply as synthesized speech.