Add new file

Dockerfile

+# This file is a template, and might need editing before it works on your project.
+# This Dockerfile installs a compiled binary into a bare system.
+# You must either commit your compiled binary into source control (not recommended)
+# or build the binary first as part of a CI/CD pipeline.
+
+FROM buildpack-deps:jessie
+
+
+import os
+import io
+import json
+import time
+import pyaudio
+import speech_recognition as sr
+from google.cloud import speech_v1p1beta1
+from google.cloud import translate
+
+# Set your Google Cloud JSON key file path
+os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = "path/to/your-key-file.json"
+
+def record_audio():
+    audio = pyaudio.PyAudio()
+    stream = audio.open(format=pyaudio.paInt16, channels=1, rate=16000, input=True, frames_per_buffer=1024)
+    frames = []
+    print("Listening...")
+
+    try:
+        while True:
+            data = stream.read(1024)
+            frames.append(data)
+    except KeyboardInterrupt:
+        print("Recording stopped.")
+    finally:
+        stream.stop_stream()
+        stream.close()
+        audio.terminate()
+
+    return b''.join(frames)
+
+def speech_to_text(audio_data):
+    client = speech_v1p1beta1.SpeechClient()
+    config = {
+        "language_code": "en-US",
+    }
+    audio = {"content": audio_data}
+    response = client.recognize(config=config, audio=audio)
+    return response.results[0].alternatives[0].transcript
+
+def translate_text(text):
+    client = translate.TranslationServiceClient()
+    parent = client.location_path("your-project-id", "global")
+    response = client.translate_text(
+        parent=parent,
+        contents=[text],
+        target_language_code="si",  # Sinhala language code
+    )
+    return response.translations[0].translated_text
+
+if __name__ == "__main__":
+    audio_data = record_audio()
+    transcribed_text = speech_to_text(audio_data)
+    print("Transcribed Text:", transcribed_text)
+
+    translated_text = translate_text(transcribed_text)
+    print("Translated Text (Sinhala):", translated_text)
+
+
+
+import deepspeech
+import wave
+import numpy as np
+
+# Load the DeepSpeech model
+model = deepspeech.Model("path/to/your/model.pb")
+
+# Create a stream for audio input
+ds_stream = model.createStream()
+
+# Open an audio file for recognition
+audio_file = "path/to/your/sinhala_audio.wav"
+
+# Read the audio file and recognize the text
+with wave.open(audio_file, "rb") as wf:
+    rate = wf.getframerate()
+    audio_data = wf.readframes(wf.getnframes())
+    audio_data = np.frombuffer(audio_data, np.int16)
+    text = model.stt(audio_data)
+    print("Recognized Text (Sinhala):", text)
+
+
+WORKDIR /usr/local/bin
+
+# Change `app` to whatever your binary is called
+Add app .
+CMD ["./app"]