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Found 12 papers, 1 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.
Exploring the Impact of Noise and Degradations on Heart Sound Classification Models
We used this dataset to investigate the impact of noise and degradation in heart sound recordings on the performance of different classification models.
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.
Supervised Learning based QoE Prediction of Video Streaming in Future Networks: A Tutorial with Comparative Study
The Quality of Experience (QoE) based service management remains key for successful provisioning of multimedia services in next-generation networks such as 5G/6G, which requires proper tools for quality monitoring, prediction and resource management where machine learning (ML) can play a crucial role.
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.
WARP-Q: Quality Prediction For Generative Neural Speech Codecs
Good speech quality has been achieved using waveform matching and parametric reconstruction coders.
How deep is your encoder: an analysis of features descriptors for an autoencoder-based audio-visual quality metric
The development of audio-visual quality assessment models poses a number of challenges in order to obtain accurate predictions.
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.
