Search Results for author:
Found 8 papers, 0 papers with code
Dialogue Understandability: Why are we streaming movies with subtitles?
Watching movies and TV shows with subtitles enabled is not simply down to audibility or speech intelligibility.
Reduce, Reuse, Recycle: Is Perturbed Data better than Other Language augmentation for Low Resource Self-Supervised Speech Models
Our findings suggest that for resource constrained languages, in-domain synthetic augmentation can outperform knowledge transfer from accented or other language speech.
Learning Music Representations with wav2vec 2.0
In addition, the results are superior to the pre-trained model on speech embeddings, demonstrating that wav2vec 2. 0 pre-trained on music data can be a promising music representation model.
Using Rater and System Metadata to Explain Variance in the VoiceMOS Challenge 2022 Dataset
Non-reference speech quality models are important for a growing number of applications.
A Comparison of Deep Learning MOS Predictors for Speech Synthesis Quality
In this paper, we evaluate several MOS predictors based on wav2vec 2. 0 and the NISQA speech quality prediction model to explore the role of the training data, the influence of the system type, and the role of cross-domain features in SSL models.
Exploring the influence of fine-tuning data on wav2vec 2.0 model for blind speech quality prediction
Further research is needed to evaluate other wav2vec 2. 0 models pre-trained with multi-lingual datasets and to develop prediction models that are more resilient to language diversity.
More for Less: Non-Intrusive Speech Quality Assessment with Limited Annotations
This paper indicates that multi-task learning combined with feature representations from unlabelled data is a promising approach to deal with the lack of large MOS annotated datasets.
Audio Impairment Recognition Using a Correlation-Based Feature Representation
Audio impairment recognition is based on finding noise in audio files and categorising the impairment type.
