ngChat Speech SDK: Client for ngChat speech recognition and speech synthesis.
Project description
ngChat Speech SDK
Please contact info@seasalt.ai if you have any questions.
Speech-to-Text Example:
Prerequisites
You will need a ngChat speech service account to run this example. Please contact info@seasalt.ai and apply for it.
Install and import
To install ngChat Speech SDK:
pip install ngchat-speech-sdk
To import ngChat Speech SDK:
import ngchat_speech.speech as speechsdk
Recognition
In the example below, we show how to recognize speech from an audio file. You can also apply recognition to an audio stream.
Speech Configuration
Use the following code to create SpeechConfig
(contact info@seasalt.ai for the speech service account):
speech_config = speechsdk.SpeechConfig(
account_id=NGCHAT_ACCOUNT,
password=PASSWORD
)
Audio Configuration
Use the following code to create AudioConfig
.
# Code commented out is an example for recognition on an audio stream.
# audio_format = speechsdk.audio.AudioStreamFormat(
# samples_per_second=16000, bits_per_sample=16, channels=1)
# audio_stream = speechsdk.audio.PushAudioInputStream(stream_format=audio_format)
# audio_config = speechsdk.audio.AudioConfig(stream=audio_stream)
audio_config = speechsdk.audio.AudioConfig(filename="test.wav")
Recognizer initialization
SpeechRecognizer can be initialzed as follows:
speech_recognizer = speechsdk.SpeechRecognizer(
speech_config=speech_config,
audio_config=audio_config
)
Callbacks connection
SpeechRecognizer has 5 kinds of callbacks:
- Recognizing - called when recognition is in progress.
- Recognized - called when a single utterance is recognized.
- Canceled - called when a continuous recognition is interrupted.
- Session_started - called when a recognition session is started.
- Session_stopped - called when a recognition session is stopped.
To connect the callbacks:
speech_recognizer.recognizing.connect(
lambda evt: print(f"Recognizing: {evt.result.text}"))
speech_recognizer.recognized.connect(
lambda evt: print(f'Recognized: {evt.result.text}'))
speech_recognizer.canceled.connect(
lambda evt: print(f'Canceled: {evt}'))
speech_recognizer.session_started.connect(
lambda evt: print(f'Session_started: {evt}'))
speech_recognizer.session_stopped.connect(
lambda evt: print(f'Session_stopped: {evt}'))
Recognizing speech
Now it is ready to run SpeechRecognizer. SpeechRecognizer has two ways for speech recognition:
- Single-shot recognition - Performs recognition once. This is to recognize a single audio file. It stops recognition after a single utterance is recognized.
- Continuous recognition (async) - Asynchronously initiates continuous recognition on an audio stream. Recognition results are available through callback functions. To stop the continuous recognition, call
stop_continuous_recognition_async()
.
# Code commented out is for recognition on an audio stream.
# speech_recognizer.start_continuous_recognition_async()
speech_recognizer.recognize_once()
Putting everything together
Now, put everything together and run the example:
import speech as speechsdk
import audio as audio
import asyncio
import threading
import sys
import time
if __name__=="__main__":
# this is an example to show how to use the ngChat Speech SDK to recognize once
try:
speech_config = speechsdk.SpeechConfig(
account_id=NGCHAT_ACCOUNT,
password=PASSWORD
)
audio_config = audio.AudioConfig(filename="test.wav")
speech_recognizer = speechsdk.SpeechRecognizer(
speech_config=speech_config,
audio_config=audio_config
)
speech_recognizer.recognizing.connect(
lambda evt: print(f"Recognizing: {evt.result.text}"))
speech_recognizer.recognized.connect(
lambda evt: print(f'Recognized: {evt.result.text}'))
speech_recognizer.canceled.connect(
lambda evt: print(f'Canceled: {evt}'))
speech_recognizer.session_started.connect(
lambda evt: print(f'Session_started: {evt}'))
speech_recognizer.session_stopped.connect(
lambda evt: print(f'Session_stopped: {evt}'))
speech_recognizer.recognize_once()
time.sleep(3)
except KeyboardInterrupt:
print("Caught keyboard interrupt. Canceling tasks...")
except Exception as e:
print(f"Exception: {e}")
finally:
sys.exit()
Text-to-Speech Example:
Prerequisites
You will need a ngChat speech service account to run this example. Please contact info@seasalt.ai and apply for it.
Install and import
To install ngChat Speech SDK:
pip install ngchat-speech-sdk
To import ngChat Speech SDK:
import ngchat_speech.speech as speechsdk
Synthesis
In the example below, we show how to synthesize text to generate an audio file. You can also receive synthesis results from an audio stream.
Speech Configuration
Use the following code to create SpeechConfig
(contact info@seasalt.ai for the speech service account):
speech_config = speechsdk.SpeechConfig(
account_id=NGCHAT_ACCOUNT,
password=PASSWORD
)
Audio Configuration
Use the following code to create AudioOutputConfig
.
import ngchat_speech.audio as audio
# Code commented out is an example for receiving synthesis results from an audio stream.
# audio_stream = audio.AudioOutputStream()
# audio_config = audio.AudioOutputConfig(stream=audio_stream)
audio_config = audio.AudioOutputConfig(filename="output.wav")
Synthesizer initialization
Synthesizer can be initialzed as follows:
speech_synthesizer = speechsdk.SpeechSynthesizer(
speech_config=speech_config,
audio_config=audio_config
)
Callbacks connection
SpeechSynthesizer has 4 kinds of callbacks:
- Synthesis_started - called when synthesis is started.
- Synthesizing - called when each time part of synthesis result is given.
- Synthesis_completed - called when all text was synthesized.
- Synthesis_canceled - called when synthesis is interrupted.
To connect the callbacks:
speech_synthesizer.synthesis_started.connect(
lambda : print("synthesis started"))
speech_synthesizer.synthesizing.connect(
lambda audio_data: print("synthesizing"))
speech_synthesizer.synthesis_completed.connect(
lambda audio_data: print("synthesis completed"))
speech_synthesizer.synthesis_canceled.connect(
lambda : print("synthesis canceled"))
Synthesizing text
Now it is ready to run SpeechSynthesizer. There are two ways to run SpeechSynthesizer:
- Synchronized - Perform synthesis until got all result.
- Asynchronized - Start synthesis and return a
speechsdk.ResultFuture
, which you could call itsget()
function to wait and get synthesis result.
# Code commented out is for synchronized synthesis
# result = speech_synthesizer.speak_text("Input your text to synthesize here.")
result = speech_synthesizer.speak_text_async("Input your text to synthesize here.").get()
# Code commented out is an example for reading synthesis result from an audio stream.
# audio_data = audio_stream.read()
Judge result reason --> Check result
Both the synchronized and asynchronized methods return a speechsdk.SpeechSynthesisResult
object, which indicates if synthesis was completed successfully:
if result.reason == speechsdk.ResultReason.ResultReason_SynthesizingAudioCompleted:
print("finished speech synthesizing")
Putting everything together
Now, put everything together and run the example:
from ngchat_speech import speech as speechsdk
from ngchat_speech import audio as audio
if __name__ == "__main__":
speech_config = speechsdk.SpeechConfig(
account_id=NGCHAT_ACCOUNT,
password=PASSWORD
)
audio_config = audio.AudioOutputConfig(filename="output.wav")
speech_synthesizer = speechsdk.SpeechSynthesizer(
speech_config=speech_config,
audio_config=audio_config
)
speech_synthesizer.synthesis_started.connect(
lambda : print("synthesis started"))
speech_synthesizer.synthesizing.connect(
lambda audio_data: print("synthesizing"))
speech_synthesizer.synthesis_completed.connect(
lambda audio_data: print("synthesis completed"))
speech_synthesizer.synthesis_canceled.connect(
lambda : print("synthesis canceled"))
# result = speech_synthesizer.speak_text("Seasalt.ai is a service company focusing on multi-modal AI solutions.")
result = speech_synthesizer.speak_text_async("Seasalt.ai is a service company focusing on multi-modal AI solutions.").get()
if result.reason == speechsdk.ResultReason.ResultReason_SynthesizingAudioCompleted:
print("finished speech synthesizing")
Change Log
[0.1.14] - 2021-4-9
Improments
- Added output of post-processing result
[0.1.13] - 2021-4-1
Improments
- Added output of segment and word alignment information
[0.1.12] - 2020-12-10
Bugfixes
- Remove unused variable
Improvements
- Added websocket packages in requirements.txt file
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file ngchat-speech-sdk-0.1.16.tar.gz
.
File metadata
- Download URL: ngchat-speech-sdk-0.1.16.tar.gz
- Upload date:
- Size: 16.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.25.1 setuptools/49.2.0 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.6.9
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | f11d27eec956be586971a76d1626d8780f79feb6404dc0064333e1d1ec164129 |
|
MD5 | 7836f4ec4128380c7274251960551793 |
|
BLAKE2b-256 | 0d70f8cc6382b670b51ccc7568c6c2a3e2dc06bbd9b2065aa2ff3b0f4c14f372 |
File details
Details for the file ngchat_speech_sdk-0.1.16-py3-none-any.whl
.
File metadata
- Download URL: ngchat_speech_sdk-0.1.16-py3-none-any.whl
- Upload date:
- Size: 18.8 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.25.1 setuptools/49.2.0 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.6.9
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | ae16ef1454b3ea685cf0e00df2d6137d6644d81e59690ed11ee6fef10a46d6ec |
|
MD5 | f420c2d995d6317302600e3f03629d21 |
|
BLAKE2b-256 | 0793a4b4366591961583b8c34d682554d1a44d2ad73dc9d8d29ae3c2fc95d031 |