Voice Transcription

This Speech-to-Text application provides an interactive interface for users to record audio messages using their microphone and receive accurate transcriptions.

VIEW CODE ON GITHUB

Start the FlexAI Endpoints

Create the FlexAI secret that contains your HF token in order to access the inference models:

# Enter your HF token value when prompted
flexai secret create hf-token

Start the FlexAI endpoint of the LLM:

LLM_INFERENCE_NAME=speech2text
flexai inference serve $LLM_INFERENCE_NAME --hf-token-secret hf-token --runtime vllm-nvidia-0.10.1 -- --model=openai/whisper-large-v3

Store the returned Inference Endpoint API KEY and Endpoint URL:

export LLM_API_KEY=<store the given API key>
export LLM_URL=$(flexai inference inspect $LLM_INFERENCE_NAME -j | jq .config.endpointUrl -r)

You'll notice the last export line uses the jq  tool to extract the value of endpointUrl from the JSON output of the inspect command.

If you don't have it already, you can get jq from its official website: https://jqlang.org/

Setup

1. Navigate to the speech-to-text directory:

cd code/speech-to-text/

2. Install the required dependencies:

pip install -r requirements.txt

3. Run the application:

python main.py

The application will start and display two URLs:

• Local URL: For local access (e.g., http://127.0.0.1:7860)
• Public URL: For sharing (e.g., https://xxxxxxxxxx.gradio.live)

Usage

1. Access the Interface: Open the Gradio interface in your web browser. To avoid any microphone access permission errors, prefer to use the public URL rather than the local one.
2. Record Audio:
   
   • Click the record icon to start recording
   • Speak your message
   • Click stop when finished recording
3. Get Transcription: Click the "Transcribe" button to process your audio and receive the text transcription.
4. View Results: The transcribed text will appear in the results panel on the right side of the interface.