ASR

[DavidMacha]

Hi, everyone! I'm having a problem with the OpenAI Whisper ASR system. I've integrated it into my speech-to-text application, but the transcriptions are not as accurate as I expected. Sometimes, it misunderstands spoken phrases. Can anyone help me troubleshoot this issue?

[Mattral]

Can you share a code snippet where you're making API calls to the OpenAI Whisper system? It would be useful to see how you're interacting with the ASR model.

[DavidMacha]

import openai

# Set my API key
api_key = "my_api_key_here"
openai.api_key = api_key

# Provide an audio prompt for Whisper to transcribe
audio_prompt = "path/to/audio/file.wav"

# Make an API call to transcribe the audio
response = openai.Whisper.transcribe(
    audio=audio_prompt,
    temperature=0.8,  # I've experimented with temperature, but it hasn't improved accuracy much
)

# Print the transcription
print(response['text'])

[Mattral]

Your code looks fine. One thing to consider is the quality and format of your audio input. Whisper performs better with clear and well-recorded audio. Make sure your audio files are in a supported format and free from background noise or distortions.

[Mattral]

the temperature parameter can influence the randomness of the generated text. You might want to experiment with different temperature values to find the balance between randomness and accuracy. Lower values like 0.2 might yield more focused and deterministic results.

[Mattral]

have you considered fine-tuning the Whisper model for your specific use case? Fine-tuning can significantly enhance performance, especially if your application involves domain-specific vocabulary or accents.

[DavidMacha]

I haven't tried fine-tuning yet, but that sounds like a promising approach. I'll explore fine-tuning to see if it addresses the specific challenges in my speech-to-text application. Thanks for the suggestion!