> ## Documentation Index
> Fetch the complete documentation index at: https://docs.reverieinc.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Voice Search
> This Python script demonstrates how to implement a real-time voice search system using Reverie SDK’s Speech-to-Text (STT) service. The script captures audio input from the microphone, transcribes it into text, and processes the text for further use (such as conducting a search query, triggering actions, or further processing).
### Install Dependencies
```bash Python theme={null}
pip install pyaudio
pip install reverie-sdk
pip install python-dotenv
```
### How does it Works?
The main steps involved in the script are as follows:
1. **Environment Configuration**:
The script loads essential credentials (REVERIE\_APP\_ID and REVERIE\_API\_KEY) from environment variables using the dotenv package. These credentials are required for accessing the Reverie SDK and its services.
```python Python theme={null}
import os
import dotenv
from reverie_sdk import ReverieClient
dotenv.load_dotenv("../.env")
REVERIE_APP_ID = os.environ.get("REVERIE_APP_ID")
REVERIE_API_KEY = os.environ.get("REVERIE_API_KEY")
client = ReverieClient(
api_key=REVERIE_API_KEY,
app_id=REVERIE_APP_ID,
)
```
2. **Real-Time Audio Capture:**:
The script uses the pyaudio library to stream audio data from the microphone. The audio is captured in real-time, with the system processing 16kHz, mono audio in 16-bit signed integer format.
```python Python theme={null}
import pyaudio
import asyncio
stream = AudioStream()
pa = pyaudio.PyAudio()
def mic_callback(in_data, frame_count, time_info, status):
try:
asyncio.run(stream.add_chunk_async(in_data))
except Exception as e:
print(f"Error in mic callback: {e}")
return (None, pyaudio.paAbort)
return (None, pyaudio.paContinue)
pa_stream = pa.open(
rate=16000,
channels=1,
format=pyaudio.paInt16,
frames_per_buffer=1024,
input=True,
stream_callback=mic_callback,
)
pa_stream.start_stream()
```
3. **Speech-to-Text (STT) Conversion**:
The audio data is continuously streamed and sent to Reverie's Automatic Speech Recognition (ASR) service for transcription. The system listens for spoken words and converts them into text in the specified source language (in this case, English).
```python Python theme={null}
from reverie_sdk.services.asr import ReverieAsrResult, AudioStream
await client.asr.stt_stream_async(
src_lang=source_lang,
bytes_or_stream=stream,
callback=asr_callback,
format="16k_int16",
punctuate="true",
domain="voice_search",
)
```
4. **Voice Search Use Case:**:
The stt\_stream\_async method is used with the "voice\_search" domain. This allows the system to process and transcribe speech, making it ideal for voice search applications where users speak their search queries, and the system translates those queries into text for further action.
```python Python theme={null}
await client.asr.stt_stream_async(
src_lang=source_lang,
bytes_or_stream=stream,
callback=asr_callback,
format="16k_int16",
punctuate="true",
domain="voice_search",
)
```
5. **Real-Time Transcription:**:
The transcription occurs in real-time, with each segment of speech being converted into text and displayed immediately. Once the system recognizes a complete, final transcription, the result is returned and printed.
```python Python theme={null}
async def speech_to_text(source_lang):
asr_responses: list[ReverieAsrResult] = []
def asr_callback(resp: ReverieAsrResult):
print(resp)
asr_responses.append(resp)
while True:
if len(asr_responses) == 0:
continue
if asr_responses[-1].final:
print(asr_responses[-1].display_text)
return asr_responses[-1].display_text
```
6. **Error Handling:**:
The script includes error handling to manage potential issues during the audio capture, streaming, and transcription process, ensuring the system continues functioning smoothly in case of interruptions.
```
import traceback
try:
# [Audio streaming and transcription code]
except Exception as err:
print(f"Error in Speech-to-Text: {err}")
traceback.print_exc()
finally:
pa_stream.stop_stream()
pa_stream.close()
```
7. **Output**:
The final transcribed text is printed to the console, which could then be used for various purposes, such as initiating a search query, performing a task, or further processing based on the transcription result.
### Sample Code
```python Python theme={null}
import asyncio
import os
import traceback
import pyaudio
from reverie_sdk import ReverieClient
from reverie_sdk.services.asr import ReverieAsrResult, AudioStream
import dotenv
dotenv.load_dotenv("../.env")
REVERIE_APP_ID = os.environ.get("REVERIE_APP_ID")
REVERIE_API_KEY = os.environ.get("REVERIE_API_KEY")
client = ReverieClient(
api_key=REVERIE_API_KEY,
app_id=REVERIE_APP_ID,
)
async def speech_to_text(source_lang):
stream = AudioStream()
pa = pyaudio.PyAudio()
def mic_callback(in_data, frame_count, time_info, status):
try:
asyncio.run(stream.add_chunk_async(in_data))
except Exception as e:
print(f"Error in mic callback: {e}")
return (None, pyaudio.paAbort)
return (None, pyaudio.paContinue)
pa_stream = pa.open(
rate=16000,
channels=1,
format=pyaudio.paInt16,
frames_per_buffer=1024,
input=True,
stream_callback=mic_callback,
)
pa_stream.start_stream()
print("Listening at STT..")
asr_responses: list[ReverieAsrResult] = []
def asr_callback(resp: ReverieAsrResult):
print(resp)
asr_responses.append(resp)
try:
await client.asr.stt_stream_async(
src_lang=source_lang,
bytes_or_stream=stream,
callback=asr_callback,
format="16k_int16",
punctuate="true",
domain="voice_search",
)
while True:
if len(asr_responses) == 0:
continue
if asr_responses[-1].final:
print(asr_responses[-1].display_text)
return asr_responses[-1].display_text
except Exception as err:
print(f"Error in Speech-to-Text: {err}")
traceback.print_exc()
finally:
pa_stream.stop_stream()
pa_stream.close()
asyncio.run(speech_to_text("en"))
```