metadata
tags:
- audio
license: apache-2.0
language:
- en
pretty_name: NonverbalTTS
size_categories:
- 1K<n<10K
configs:
- config_name: default
data_files:
- split: train
path: data/train/**
- split: dev
path: data/dev/**
- split: test
path: data/test/**
- split: other
path: data/other/**
NonverbalTTS Dataset 🎵🗣️
NonverbalTTS is a 17-hour open-access English speech corpus with aligned text annotations for nonverbal vocalizations (NVs) and emotional categories, designed to advance expressive text-to-speech (TTS) research.
Key Features ✨
- 17 hours of high-quality speech data
- 10 NV types: Breathing, laughter, sighing, sneezing, coughing, throat clearing, groaning, grunting, snoring, sniffing
- 8 emotion categories: Angry, disgusted, fearful, happy, neutral, sad, surprised, other
- Diverse speakers: 2296 speakers (60% male, 40% female)
- Multi-source: Derived from VoxCeleb and Expresso corpora
- Rich metadata: Emotion labels, NV annotations, speaker IDs, audio quality metrics
- Sampling rate: 16kHz sampling rate for audio from VoxCeleb, 48kHz for audio from Expresso
Loading the Dataset 💻
from datasets import load_dataset dataset = load_dataset("deepvk/NonverbalTTS", revision="refs/convert/parquet")Annotation Pipeline 🔧
Automatic Detection
- NV detection using BEATs
- Emotion classification with emotion2vec+
- ASR transcription via Canary model
Human Validation
- 3 annotators per sample
- Filtered non-English/multi-speaker clips
- NV/emotion validation and refinement
Fusion Algorithm
- Majority voting for final transcriptions
- Pyalign-based sequence alignment
- Multi-annotator hypothesis merging
Benchmark Results 📊
Fine-tuning CosyVoice-300M on NonverbalTTS achieves parity with state-of-the-art proprietary systems:
Metric NVTTS CosyVoice2 Speaker Similarity 0.89 0.85 NV Jaccard 0.8 0.78 Human Preference 33.4% 35.4% Use Cases 💡
- Training expressive TTS models
- Zero-shot NV synthesis
- Emotion-aware speech generation
- Prosody modeling research
License 📜
- Annotations: CC BY-NC-SA 4.0
- Audio: Adheres to original source licenses (VoxCeleb, Expresso)
Citation 📝
TODO