ss_fastAPI.py

import os
import shutil
import subprocess
from fastapi import FastAPI, File, UploadFile, Form
from fastapi.responses import FileResponse, JSONResponse
from fastapi.responses import HTMLResponse
from pydub import AudioSegment
import shutil
import tempfile
import speech_recognition as sr
import os
r = sr.Recognizer()

app = FastAPI()

def resample_audio(input_path, output_path, target_sample_rate):
    ffmpeg_cmd = [
        "ffmpeg",
        "-i", input_path,
        "-ar", str(target_sample_rate),
        output_path
    ]
    subprocess.run(ffmpeg_cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE)

@app.get("/", response_class=HTMLResponse)
async def read_root():
    # Provide the path to the HTML file containing the front-end code
    with open("soundscripter.html", "r") as file:
        html_content = file.read()
    return html_content

def get_sampling_rate(audio_file_path):
    audio = AudioSegment.from_file(audio_file_path)
    return audio.frame_rate

@app.post("/process_audio")
async def process_audio(audio: UploadFile = File(...), language: str = Form(...)):
    if not audio or not language:
        return JSONResponse(content={"success": False}, status_code=400)

    # Check if the uploaded file is in WAV format
    if audio.content_type != "audio/wav":
        return JSONResponse(content={"success": False, "message": "Audio must be in WAV format."}, status_code=400)

    try:
        # Save the received audio to a temporary file
         with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as temp_file:
            temp_file_path = temp_file.name
            shutil.copyfileobj(audio.file, temp_file)

        # Print the file path for debugging
         print(temp_file_path)
         output_path = tempfile.mktemp(suffix=".wav")

        # Resample the audio to 16000 Hz
         resample_audio(temp_file_path, output_path, target_sample_rate=16000)
         print(output_path)

        # Get the sampling rate of the received audio
         sampling_rate = get_sampling_rate(output_path)

        # Resample the audio to 16 kHz if needed
         if sampling_rate != 16000:
            return JSONResponse(content={"success": False, "message": "Sample rate is not 16000Hz."}, status_code=500)
         
         


    except Exception as e:
        print("Error processing audio:", e)
        return JSONResponse(content={"success": False, "message": "Error processing audio."}, status_code=500)
    # finally:
    #     # Cleanup: remove the temporary received audio file
    #     if os.path.exists(audio_file_path):
    #         os.remove(audio_file_path)
    return JSONResponse(content={"success": True, "language":calling_asr(output_path,"hi-IN")})

def calling_asr(wav_file,lid):
    AUDIO_FILE=wav_file
    # aud_name=AUDIO_FILE.split('/')[-1].split('.')[0]
    file=open(wav_file+".txt","w")
    text="cant read wav file"
    try:
        with sr.AudioFile(AUDIO_FILE) as source:
            audio = r.record(source)
        text = r.recognize_google(audio, language=lid)
        #file.write(aud_name +"\t"+text)
        return text
    except:
        #file.write(" "+"Error in segement"+" ")
        return text
    #file.close()