Python implementation of the client for Vatis's ASR services

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Project description

Speech recognition client for Vatis API in Python

Python implementation of the client for Vatis's ASR services

Getting started

Requirements

Python >= 3.6

Installation

Create a free account on the Vatis Platform
Obtain you're private API key
Install Vatis Live ASR client: pip install "vatis_asr_client[remote]"
Add your private key as environment variable: VATIS_ASR_CLIENT_API_KEY=<YOUR_API_KEY>
(Optional) Configure other environment variables

Usage

1. Create a stream configuration object

from vatis.live_asr.config.stream import StreamConfig, Language, SPEED_CONFIGURATION, SampleRate, Channel, \
     DEFAULT_CONNECTION_CONFIG

stream_config: StreamConfig = StreamConfig(
        language=Language.ro_RO,
        performance_config=SPEED_CONFIGURATION,
        connection_config=DEFAULT_CONNECTION_CONFIG,
        sample_rate=SampleRate.RATE_16000,
        channels=Channel.ONE,
    )

2. Create a LiveStream based on your configuration

from vatis.live_asr.stream.factory import create_stream

with create_stream(stream_config, stream_type='BLOCKING') as stream:
    # ...

3. Add a listener for the events of your stream

from vatis.live_asr.utils.observer import FormattedLiveStreamObserver

stream.add_observer(FormattedLiveStreamObserver())

4. Create your custom data generator or use any of the predefined ones

from vatis.live_asr.utils.generator import file_generator

data_generator: Generator = file_generator('<your_wav_file_path>', stream_config)

5. Pass the generator to the stream and wait until it finishes

stream.transcribe(data_generator)

stream.wait_for_transcription()

Examples

Stream a file using a stream observer

from typing import Generator

from vatis.live_asr.config.stream import StreamConfig, Language, SPEED_CONFIGURATION, SampleRate, Channel, \
    DEFAULT_CONNECTION_CONFIG
from vatis.live_asr.logging import get_logger
from vatis.live_asr.stream.factory import create_stream
from vatis.live_asr.utils.generator import file_generator
from vatis.live_asr.utils.observer import FormattedLiveStreamObserver

logger = get_logger('main')


if __name__ == '__main__':
    stream_config: StreamConfig = StreamConfig(
        language=Language.ro_RO,
        performance_config=SPEED_CONFIGURATION,
        connection_config=DEFAULT_CONNECTION_CONFIG,
        sample_rate=SampleRate.RATE_16000,
        channels=Channel.ONE,
    )

    with create_stream(stream_config, stream_type='BLOCKING') as stream:
        stream.add_observer(FormattedLiveStreamObserver())

        data_generator: Generator = file_generator('<your_wav_file_path>', stream_config)

        stream.transcribe(data_generator)

        stream.wait_for_transcription()

Streaming a file using a generator

from typing import Generator

from vatis.live_asr.config.stream import StreamConfig, Language, SPEED_CONFIGURATION, SampleRate, Channel, \
    DEFAULT_CONNECTION_CONFIG
from vatis.live_asr.logging import get_logger
from vatis.live_asr.stream.factory import create_stream
from vatis.live_asr.utils.generator import file_generator

logger = get_logger('main')


if __name__ == '__main__':
    stream_config: StreamConfig = StreamConfig(
        language=Language.ro_RO,
        performance_config=SPEED_CONFIGURATION,
        connection_config=DEFAULT_CONNECTION_CONFIG,
        sample_rate=SampleRate.RATE_16000,
        channels=Channel.ONE,
    )

    with create_stream(stream_config, stream_type='BLOCKING') as stream:
        data_generator: Generator = file_generator('<your_wav_file_path>', stream_config)

        stream.transcribe(data_generator)

        for response in stream.create_generator():
            logger.info(response.transcript)

Infinite stream from the microphone using stream observers

from typing import Generator

from vatis.live_asr.config.stream import StreamConfig, Language, SPEED_CONFIGURATION, SampleRate, Channel, \
    DEFAULT_CONNECTION_CONFIG
from vatis.live_asr.stream.factory import create_stream
from vatis.live_asr.utils.generator import microphone_generator
from vatis.live_asr.utils.observer import FormattedLiveStreamObserver

if __name__ == '__main__':
    stream_config: StreamConfig = StreamConfig(
        language=Language.ro_RO,
        performance_config=SPEED_CONFIGURATION,
        connection_config=DEFAULT_CONNECTION_CONFIG,
        sample_rate=SampleRate.RATE_16000,
        channels=Channel.ONE,
    )

    with create_stream(stream_config, stream_type='BLOCKING') as stream:
        stream.add_observer(FormattedLiveStreamObserver())

        data_generator: Generator = microphone_generator(stream_config)

        stream.transcribe(data_generator)

        stream.wait_for_transcription()

Stream from the microphone a specified amount of time using generators

import sys
from typing import Generator

from vatis.asr_commons.live.headers import FINAL_FRAME_HEADER, FRAME_START_TIME_HEADER, FRAME_END_TIME_HEADER

from vatis.live_asr.config.stream import StreamConfig, Language, SPEED_CONFIGURATION, SampleRate, Channel, \
    DEFAULT_CONNECTION_CONFIG
from vatis.live_asr.stream.factory import create_stream
from vatis.live_asr.utils.generator import microphone_generator

if __name__ == '__main__':
    stream_config: StreamConfig = StreamConfig(
        language=Language.ro_RO,
        performance_config=SPEED_CONFIGURATION,
        connection_config=DEFAULT_CONNECTION_CONFIG,
        sample_rate=SampleRate.RATE_16000,
        channels=Channel.ONE,
    )

    out = sys.stdout
    time_limit: float = 0.5 * 60

    def stop_condition(frame_count: int, starting_time: dict) -> bool:
        transcribed_time = stream_config.performance_config.frame_len * frame_count

        return transcribed_time >= time_limit

    with create_stream(stream_config, stream_type='BLOCKING') as stream:
        data_generator: Generator = microphone_generator(stream_config, stop_condition=stop_condition)

        stream.transcribe(data_generator)

        for packet in stream.create_generator():
            if packet.get_header(FINAL_FRAME_HEADER, default=False):
                out.write('FINAL  : {0:.2f} -> {1:.2f}: {2}\n'.format(
                    packet.get_header(FRAME_START_TIME_HEADER),
                    packet.get_header(FRAME_END_TIME_HEADER),
                    packet.transcript
                ))
                out.flush()
            else:
                out.write('PARTIAL: {0:.2f} -> {1:.2f}: {2}\r'.format(
                    packet.get_header(FRAME_START_TIME_HEADER),
                    packet.get_header(FRAME_END_TIME_HEADER),
                    packet.transcript
                ))
                out.flush()

Infinite stream from the microphone using stream observers and saving the output to a file

from typing import Generator

from vatis.live_asr.config.stream import StreamConfig, Language, SPEED_CONFIGURATION, SampleRate, Channel, \
    DEFAULT_CONNECTION_CONFIG
from vatis.live_asr.stream.factory import create_stream
from vatis.live_asr.utils.generator import microphone_generator
from vatis.live_asr.utils.observer import FormattedLiveStreamObserver

if __name__ == '__main__':
    stream_config: StreamConfig = StreamConfig(
        language=Language.ro_RO,
        performance_config=SPEED_CONFIGURATION,
        connection_config=DEFAULT_CONNECTION_CONFIG,
        sample_rate=SampleRate.RATE_16000,
        channels=Channel.ONE
    )

    output_transcription_file: str = 'path/to/your/output_transcription.txt'

    with create_stream(stream_config, stream_type='BLOCKING') as stream:
        with open(output_transcription_file, 'w') as out:
            stream.add_observer(FormattedLiveStreamObserver())  # writes the transcript to stdout
            stream.add_observer(FormattedLiveStreamObserver(out, only_finals=True))  # writes the transcript to the output file

            data_generator: Generator = microphone_generator(stream_config)

            stream.transcribe(data_generator)

            stream.wait_for_transcription()

Custom models

Use a pre-defined model for a specific language

from vatis.live_asr.config.stream import StreamConfig, Language, SPEED_CONFIGURATION, SampleRate, Channel, \
     DEFAULT_CONNECTION_CONFIG
from vatis.asr_commons.custom_models import ro_RO

stream_config: StreamConfig = StreamConfig(
        language=Language.ro_RO,
        performance_config=SPEED_CONFIGURATION,
        connection_config=DEFAULT_CONNECTION_CONFIG,
        sample_rate=SampleRate.RATE_16000,
        channels=Channel.ONE,
        model=ro_RO.MEDIA
)

Use your own custom model. Contact us for details about how to build your own custom model.

from vatis.live_asr.config.stream import StreamConfig, Language, SPEED_CONFIGURATION, SampleRate, Channel, \
     DEFAULT_CONNECTION_CONFIG

stream_config: StreamConfig = StreamConfig(
        language=Language.ro_RO,
        performance_config=SPEED_CONFIGURATION,
        connection_config=DEFAULT_CONNECTION_CONFIG,
        sample_rate=SampleRate.RATE_16000,
        channels=Channel.ONE,
        model='00000000-0000-0000-0000-000000000000'
)

Environment variables

Variable	Type	Default value	Description
VATIS_ASR_CLIENT_DEBUG	bool	False	Debug flag for more logging
VATIS_ASR_CLIENT_RECONNECTION_ATTEMPTS	int	6	Maximum connection attempts to the ASR service
VATIS_ASR_CLIENT_REQUEST_TIMEOUT_SECONDS	float	15	Timeout of an attempt to make a request to the server
VATIS_ASR_CLIENT_RECONNECTION_DELAY_SECONDS	float	5	Delay between two reconnection attempts
VATIS_ASR_CLIENT_CONNECTION_TIMEOUT_SECONDS	float	10	Timeout of a connection attempt
VATIS_ASR_CLIENT_SERVICE_HOST	string	a5111be014375425f9cfe48e23715c8c-6ed9fe3966df7ef3.elb.eu-central-1.amazonaws.com	ASR service host name
VATIS_ASR_CLIENT_SERVICE_PORT	int	80	ASR service port number
VATIS_ASR_CLIENT_AUTHENTICATION_PROVIDER_URL	string	https://vatis.tech/api/v1/asr-client/auth	Authentication end-point
VATIS_ASR_CLIENT_API_KEY	string		Private API key for ASR service access
VATIS_ASR_CLIENT_LOGS_FILE	string	logs/app.logs	Path for storing log files
VATIS_ASR_CLIENT_ENABLE_LOGS_FILE	bool	False	Flag for enabling logs storing inside files

Project details

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This version

1.2.0

Dec 2, 2021

1.1.1

Oct 7, 2021

1.0.5

Sep 21, 2021

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