pip install livestt # this could take a while
Livestt gives access to 3 main classes/functions.
from livestt import wait
def callback_func():
print("Wakeword said!")
wait(callback=callback_func)
The wait
function takes in these args:
callback
(Callable): The function to be called when the wake word is detected.
args
(tuple[any] | None): The arguments to be passed to the callback function. The default is None.
wake_word
(str): The wake word that the function is waiting for. The default is "Sheila".
prob_threshold
(float): The probability threshold for the wake word detection. The default is 0.5.
chunk_length_s
(float): The length of the audio chunk to be processed at a time, in seconds. The default is 2.0.
stream_chunk_s
(float): The length of the audio stream chunk to be processed at a time, in seconds. The default is 0.25.
debug
(bool): If True, debug information will be printed. The default is True.
Raises:
ValueError
: If the wake word is not in the set of valid class labels.
Returns:
None
from livestt import Recorder
import time
recorder = Recorder("test.wav")
recorder.start() # Starts recorder thread
time.sleep(5) # Waits before ending thread
recorder.end() # Writes recording to "test.wav"
The Recorder
class when started starts a new recorder thread where it will listen to the audio until the thread is ended. Upon the thread ending, the recording will be saved to a file. The Recorder
class takes these args:
chunk
(int): The number of audio frames per buffer.
format
(int): The sample format for the recording.
channels
(int): The number of channels for the recording.
fs
(int): The sample rate of the recording.
filename
(str): The name of the output file where the recording will be saved. The file_ MUST currently be .wav
listening
(bool): A flag indicating whether the recorder is currently recording.
from livestt import transcribe
transcription = transcribe("test.wav")
for t in transcription:
print(t.text)
The transcribe
function transcribes the given audio file and outputs the transcribed text along with other information. The transcribe
function takes these args:
input_file
(str): The path to the audio file to be transcribed.
language
(str): The language of the audio file. The default is "en" (English).
model_name
(str): The name of the model to be used for transcription. The default is "tiny.en".
This function yields a tuple with the following fields:
text
(str): The transcribed text.
language_probability
(float): The probability of the detected language.
language
(str): The detected language.
segment_end
(float): The end time of the transcribed segment.
segment_start
(float): The start time of the transcribed segment.
For a full example, check out the example in the file example/main.py
.
- Pyaudio for recording audio.
- faster-whisper for transcription.
- openWakeWord for wakeword detection.
Thanks to Kolja for the inspiration. I couldn't figure out how to use his library so I made my own. Check this out here.
Contributions are always welcome! Open an issue or make a PR. Or just contact me on discord: @a3l6