arXiv AI
Jun 8
dots.tts Technical Report
arXiv:2606. 07080v1 Announce Type: cross Abstract: We present dots.
TokAN: Accent Normalization Using Self-Supervised Speech Tokens
arXiv:2607. 03928v1 Announce Type: cross Abstract: Accent normalization (AN) seeks to convert non-native (L2) accented speech into standard (L1) speech while preserving speaker identity.
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arXiv AI
Jun 9
End-to-End Training for Discrete Token LLM based TTS System
arXiv:2606. 09234v1 Announce Type: cross Abstract: Recent state-of-the-art (SOTA) text-to-speech (TTS) systems typically adopt a cascaded pipeline consisting of a speech tokenizer, an autoregressive large language model (LLM), and a diffusion based flow-matching (FM) model, with these components trained independently.
arXiv AI
Jun 16
LM-SPT: LM-Aligned Semantic Distillation for Speech Tokenization
arXiv:2506. 16738v2 Announce Type: replace-cross Abstract: With the rapid progress of speech language models (SLMs), discrete speech tokens have emerged as a core interface between speech and text, enabling unified modeling across modalities.
Hugging Face Trending Papers
Aug 12
Confucius4-TTS: Transcript-Free Cross-Lingual Zero-Shot TTS with a Learnable Speaker Encoder
Recent advances in zero-shot text-to-speech (TTS) have substantially improved speech quality and voice cloning fidelity. However, many zero-shot TTS systems still depend on audio prompt transcripts at inference time.
arXiv AI
Jun 2
DSA-Tokenizer: Disentangled Semantic-Acoustic Tokenization via Flow Matching-based Hierarchical Fusion
arXiv:2601. 09239v5 Announce Type: replace-cross Abstract: Speech tokenizers are a key building block of fully discrete Speech LLMs.
arXiv Machine Learning
Jun 16
Scaling Human and G2P Supervision for Robust Phonetic Transcription
arXiv:2606. 16019v1 Announce Type: cross Abstract: Expert phonetic annotation is costly, especially for non-standard dialects and atypical speech.
arXiv AI
Jun 9
GenTSE: Enhancing Target Speaker Extraction via a Coarse-to-Fine Generative Language Model
arXiv:2512. 20978v2 Announce Type: replace-cross Abstract: Language Model (LM)-based generative modeling has emerged as a promising direction for TSE, offering potential for improved generalization and high-fidelity speech.
arXiv AI
Jun 9
BareWave: Waveform-Native Flow-Matching Text-to-Speech
arXiv:2606. 09048v1 Announce Type: cross Abstract: Removing intermediate representations and separately trained decoding stages has become an important direction in generative modeling.
arXiv Machine Learning
Jun 16
Contrastive Regularization for Accent-Robust ASR
arXiv:2605. 03297v2 Announce Type: replace-cross Abstract: ASR systems based on self-supervised acoustic pretraining and CTC fine-tuning achieve strong performance on native speech but remain sensitive to accent variability.
arXiv AI
Jul 7
ProPS: Prompted Profile Synthesis for Natural Language-Conditioned Speaker Embedding Distributions
arXiv:2607. 05276v1 Announce Type: cross Abstract: Speaker embeddings, or x-vectors, are widely used to represent speaker identity and speaker-related attributes, but existing embedding extractors are typically descriptive rather than generative: they map an observed speech segment to an x-vector, which is then used for downstream applications.
arXiv AI
Jul 7
Speaker-Disentangled Chunk-Wise Regression for Syllabic Tokenization
arXiv:2607. 04064v1 Announce Type: cross Abstract: Unsupervised syllabic tokenization aims to learn discrete syllabic tokens that capture latent linguistic content-related structure from raw speech.
arXiv AI
Aug 3
Stable Autoregressive Speech Generation with Low-Frame-Rate High-Dimensional Continuous Tokens
arXiv:2607. 29363v1 Announce Type: cross Abstract: Balancing sequence length, representational capacity, and long-horizon stability is a central problem in autoregressive (AR) speech and audio generation.