techwithanirudh/gorkie/voice

Voice

Use this skill for speech-to-text and text-to-speech tasks in the sandbox. Keep generated and converted files under /home/user/downloads unless the user asks for another path.

Text to speech

Use gtts to turn text into an MP3.

python3 - <<'PY'
from gtts import gTTS
 
text = """Replace this with the text to speak."""
gTTS(text=text, lang="en").save("/home/user/downloads/voice-message.mp3")
print("/home/user/downloads/voice-message.mp3")
PY

For Slack-friendly output, prefer MP3 or M4A. Convert with ffmpeg when needed:

ffmpeg -y -i /home/user/downloads/voice-message.mp3 -c:a aac /home/user/downloads/voice-message.m4a

Speech to text

First convert the source audio to mono WAV, then transcribe it.

ffmpeg -y -i /home/user/downloads/audio_clip.m4a -ac 1 -ar 16000 /home/user/downloads/audio_clip.wav

python3 - <<'PY'
import speech_recognition as sr
 
path = "/home/user/downloads/audio_clip.wav"
recognizer = sr.Recognizer()
 
with sr.AudioFile(path) as source:
    audio = recognizer.record(source)
 
try:
    print(recognizer.recognize_google(audio))
except sr.UnknownValueError:
    print("Could not understand audio.")
except sr.RequestError as error:
    print(f"Speech recognition request failed: {error}")
PY

Guidelines

• Use get_file first when the audio came from Slack, then work with the downloaded path.
• Use upload_file when the user wants the generated audio sent back to Slack.
• Mention when transcription uses Google's free recognizer, because it sends audio to an external service.
• For private or sensitive audio, ask before using network transcription. If an API key or local model is later available, prefer that path.
• Use ffmpeg for conversion, trimming, sample-rate changes, and audio diagnostics.
• If transcription fails, report whether the problem appears to be format conversion, silence/noise, or recognizer/API failure.