arXiv AI
Jul 9
Gradient-Based Speech-to-Text Alignment for Any ASR Model: From CTC to Speech LLMs
arXiv:2607. 06831v1 Announce Type: cross Abstract: Speech-to-text alignment means finding the temporal boundaries of each word in the audio.
Noise-Robust Forced Alignment for Spontaneous Speech
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arXiv Computation and Language
Oct 9
FA-Bench: A Benchmark for Phone- and Word-Level Timestamp Accuracy in Forced Alignment and ASR on Clean and Noisy Speech
FA-Bench is an open framework that standardizes forced alignment evaluation by fixing transcript normalization, data splits, phone mapping, and scoring procedures. It offers two tracks: one with reference transcripts and another with recognizer outputs, evaluated on clean and four degraded audio conditions using 21 open models and 9 commercial APIs. The benchmark scores every utterance boundary with a tolerance‑based F1 metric, revealing systematic timing biases such as Whisper’s 150 ms early alignment and commercial APIs’ 50 ms late alignment.
arXiv AI
Jul 24
Phonetic forced alignment for low-resource language varieties: Model training and evaluation on Chengdu Mandarin
arXiv:2607. 21332v1 Announce Type: cross Abstract: Phonetic forced alignment is a key technique in phonetic research, yet existing alignment systems lack specialized models for low-resource language varieties.
Hugging Face Trending Papers
Jul 23
Phonetic forced alignment for low-resource language varieties: Model training and evaluation on Chengdu Mandarin
Phonetic forced alignment is a key technique in phonetic research, yet existing alignment systems lack specialized models for low-resource language varieties. We address this by training text-dependent and text-independent aligners for Chengdu Mandarin using a 17-hour corpus and a custom G2P dictionary.
arXiv Machine Learning
Jul 20
RobustSpeechFlow: Learning Robust Text-to-Speech Trajectories via Augmentation-based Contrastive Flow Matching
arXiv:2605. 22083v2 Announce Type: replace-cross Abstract: While flow-matching text-to-speech (TTS) achieves strong zero-shot speaker similarity and naturalness, it remains susceptible to content fidelity issues, particularly skip and repeat errors from imperfect alignment.
arXiv Computation and Language
Aug 25
Mitigating Speaker Leakage in Cascaded Multi-talker ASR with Diarization-based Transcript Correction
arXiv:2608.22196v1 Announce Type: cross Abstract: While cascaded multi-talker ASR (MT-ASR) leverages state-of-the-art foundation models, its performance is often capped by speaker leakage during sepa...
arXiv Computation and Language
Sep 10
StreamAlign: Streaming Text-Aligned Speech Tokenization
arXiv:2609.09719v1 Announce Type: new Abstract: Text-aligned speech tokenization methods have emerged to better align speech tokens with LLM token spaces, enabling more effective utilization of pretr...
arXiv AI
Oct 15
AlignAudio: A Unified Dual-Alignment Framework for Noise-Robust Speech-Conditioned Generation
arXiv:2610.14697v1 Announce Type: cross Abstract: Speech-conditioned generation maps speech signals to target audio outputs. Prior end-to-end speech-conditioned generative models achieve high fidelit...
Hugging Face Trending Papers
Sep 9
StreamAlign: Streaming Text-Aligned Speech Tokenization
Text-aligned speech tokenization methods have emerged to better align speech tokens with LLM token spaces, enabling more effective utilization of pretrained LLMs. However, they rely on offline automat...
Hugging Face Trending Papers
Sep 8
ConversationalVoice: Full-Duplex Speech Data from Real Conversations through Source-Faithful Reconstruction and Conversation-Grounded Expansion
Full-duplex speech models require training data that preserves turn-taking, overlap, interruption, and backchannel behavior, yet these signals are entangled across speakers in noisy real-world recordi...
arXiv Computation and Language
Aug 31
Phoneme- and Word-Level Metrics Using Self-Supervised Speech Representations for Forced Alignment Evaluation
The paper introduces two new corpus‑level, reference‑free metrics—Phoneme‑Cluster Mutual Information (PCMI) and Word Acoustic Consistency Score (WACS)—that use self‑supervised speech representations to evaluate forced alignment quality. PCMI quantifies how well aligned phoneme labels agree with clusters derived from SSL representations, while WACS assesses consistency across repeated word realizations via dynamic time warping of word representation sequences. Experiments on 85 languages from FLEURS and 45 languages in DoReCo show that both metrics degrade predictably under alignment perturbations, effectively distinguish high‑ from low‑quality alignments, and correlate strongly with traditional timestamp‑based measures, enabling scalable, multilingual alignment evaluation without manual annotations.
arXiv Computer Vision
Oct 2
Align Then Reason: A Multimodal Lip-Sync Judge for Dubbing
The paper introduces Align Then Reason (ATR), a multilingual lip‑sync judge that aligns frame‑level lip representations with phonetic units of a candidate text line and then uses a language model to evaluate both content and timing. ATR achieves significant improvements over existing baselines on a seven‑language benchmark, with mean AUC gains of up to 59.4% for 2B reasoners and similar gains across other LLM families. The method also transfers well to unseen languages and outperforms lip‑reading baselines on real dubbing tasks such as dub‑line reranking and script‑to‑clip assignment.