ASR TalkNet Aligner
Model
ASR TalkNet Aligner

Text/Audio aligner based on QuartzNet 5x5 for durations extraction

Model Overview

ASR-based text/audio aligner based on CTC-loss algorithm that was used to train TalkNet.

Usage

Automatically load the model from NGC

from nemo.collections.asr.models import EncDecCTCModel
model = EncDecCTCModel.from_pretrained("asr_talknet_aligner")

For an example, on how to use this model to generate speech, refer to the TTS inference notebook.

Training Set

This model is trained on LibriTTS sampled at 22050Hz with input text converted to phonemes, and can be used to extract durations for audio excerpt and corresponding phonemes sequence.

References

[2] TalkNet 2 Paper

Publisher
Latest Version1.0.0rc1
UpdatedApril 4, 2023 UTC
Compressed Size28.82 MB

NVIDIA uses cookies to improve your experience on our web site. We and our third-party partners also use cookies and other tools to collect and record information you provide as well as information about your interactions with our websites for performance improvement, analytics, and to assist in marketing efforts. By clicking "Accept All", you consent to our use of cookies and other tools as described in our Cookie Policy. You can manage your cookie settings by clicking on "Manage Settings." By continuing to use this site or by clicking one of the buttons below, you agree to our Terms of Service (which contains important waivers). Please see our Privacy Policy for more information on our privacy practices.