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Found 10 papers, 1 papers with code
Speech Rhythm-Based Speaker Embeddings Extraction from Phonemes and Phoneme Duration for Multi-Speaker Speech Synthesis
This paper proposes a speech rhythm-based method for speaker embeddings to model phoneme duration using a few utterances by the target speaker.
What Do Self-Supervised Speech and Speaker Models Learn? New Findings From a Cross Model Layer-Wise Analysis
Our analysis unveils that 1) the capacity to represent content information is somewhat unrelated to enhanced speaker representation, 2) specific layers of speech SSL models would be partly specialized in capturing linguistic information, and 3) speaker SSL models tend to disregard linguistic information but exhibit more sophisticated speaker representation.
Noise-robust zero-shot text-to-speech synthesis conditioned on self-supervised speech-representation model with adapters
The zero-shot text-to-speech (TTS) method, based on speaker embeddings extracted from reference speech using self-supervised learning (SSL) speech representations, can reproduce speaker characteristics very accurately.
StyleCap: Automatic Speaking-Style Captioning from Speech Based on Speech and Language Self-supervised Learning Models
The experimental results demonstrate that our StyleCap leveraging richer LLMs for the text decoder, speech self-supervised learning (SSL) features, and sentence rephrasing augmentation improves the accuracy and diversity of generated speaking-style captions.
SpeechGLUE: How Well Can Self-Supervised Speech Models Capture Linguistic Knowledge?
Self-supervised learning (SSL) for speech representation has been successfully applied in various downstream tasks, such as speech and speaker recognition.
Zero-shot text-to-speech synthesis conditioned using self-supervised speech representation model
This paper proposes a zero-shot text-to-speech (TTS) conditioned by a self-supervised speech-representation model acquired through self-supervised learning (SSL).
SIMD-size aware weight regularization for fast neural vocoding on CPU
Pruning time-consuming DNN modules is a promising way to realize a real-time vocoder on a CPU (e. g. WaveRNN, LPCNet).
Model architectures to extrapolate emotional expressions in DNN-based text-to-speech
In this study, the meaning of "extrapolate emotional expressions" is to borrow emotional expressions from others, and the collection of emotional speech uttered by target speakers is unnecessary.
DNN-based Speech Synthesis Using Abundant Tags of Spontaneous Speech Corpus
In this paper, we investigate the effectiveness of using rich annotations in deep neural network (DNN)-based statistical speech synthesis.
V2S attack: building DNN-based voice conversion from automatic speaker verification
The experimental evaluation compares converted voices between the proposed method that does not use the targeted speaker's voice data and the standard VC that uses the data.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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