A Python package for audio visualization and playback in Jupyter notebooks.
- Visualize audio waveforms in Jupyter notebooks
- Support for various audio formats (WAV, MP3, FLAC, etc.)
- Streaming audio playback for real-time applications
- Programmatic control with play/pause functionality
- Performance monitoring with latency and RTF metrics
- Display alignment information on waveforms
pip install wavesurferPlay a wave file directly:
from wavesurfer import play
play("assets/test_16k.wav")
Play waveform data:
from audiolab import load_audio
from wavesurfer import play
audio, rate = load_audio("assets/test_16k.wav")
play(audio, rate)Display alignment information on the waveform:
from wavesurfer import play
# Play with alignment information from a TextGrid file
play("assets/test_16k.wav", alignments="assets/test_16k.TextGrid", config={"options": {"normalize": True}})
You can also provide alignments as a list of alignment items:
from wavesurfer import play
# Create alignment items
alignments = [
{"start": 0.0, "end": 0.5, "content": "hello"},
{"start": 0.5, "end": 1.0, "content": "world"},
]
# Play with alignment information
play("assets/test_16k.wav", alignments=alignments)Play streaming waveform data:
import time
from audiolab import load_audio
from wavesurfer import play
def audio_generator():
frame_size = int(0.3 * 16000)
for frame, _ in load_audio("assets/test_16k.wav", frame_size=frame_size):
time.sleep(0.1) # RTF: 0.1 / 0.3 < 1
yield frame
play(audio_generator(), 16000)For more advanced usage, you can use the Player class directly to have programmatic control over playback:
from wavesurfer import Player
# Create a player instance
player = Player()
# Load audio
player.load("assets/test_16k.wav")
# Programmatically control playback
player.play() # Start playback
player.pause() # Pause playbackThe Player class also supports all the audio formats that the play function supports, including file paths, waveform data, and streaming generators.