datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
dualturn-otospeech-turn-taking
OtoSpeech Turn-Taking
Official DualTurn release of the otospeech corpus, with per-frame turn-taking labels and
Mimi speech codec features. Each row is one full conversation. Frame rate 12.5 Hz (80 ms per frame).
Paper: DualTurn: Learning Turn-Taking from Dual-Channel Generative Speech Pretraining
Training code: github.com/anyreachai/dualturn
Model checkpoint: anyreach-ai/dualturn-qwen2.5-mimi-0.5B
Splits
Split
Sessions
train
896
val
111
test
113… See the full description on the dataset page: https://huggingface.co/datasets/anyreach-ai/dualturn-otospeech-turn-taking.dualturn-switchboard-turn-taking
Switchboard Turn-Taking
Official DualTurn release of the switchboard corpus, with per-frame turn-taking labels and
Mimi speech codec features. Each row is one full conversation. Frame rate 12.5 Hz (80 ms per frame).
Paper: DualTurn: Learning Turn-Taking from Dual-Channel Generative Speech Pretraining
Training code: github.com/anyreachai/dualturn
Model checkpoint: anyreach-ai/dualturn-qwen2.5-mimi-0.5B
Splits
Split
Sessions
train
1986
val
295
test
138… See the full description on the dataset page: https://huggingface.co/datasets/anyreach-ai/dualturn-switchboard-turn-taking.semantic-turn-taking-benchmark
Semantic Turn-Taking Benchmark
A curated evaluation benchmark for semantic turn-taking models in voice AI. Given a conversation context, predict what action the AI agent should take: speak, listen, continue speaking, or continue listening.
Unlike acoustic-based approaches (VAD, silence detection), this benchmark tests whether a model can make turn-taking decisions from text/semantic content alone.
Action Classes
Action
Description
start_speaking
User… See the full description on the dataset page: https://huggingface.co/datasets/anyreach-ai/semantic-turn-taking-benchmark.candor-turntaking-annotations
CANDOR - Turn-Taking Annotations
Speech transcription and turn-taking annotation dataset built from the CANDOR corpus using NVIDIA Canary-Qwen2.5B ASR.
Dataset Description
This dataset contains 172,591 transcribed speech segments from the CANDOR conversational speech corpus (1,656 conversations). Each segment is a per-speaker utterance with Canary ASR transcript, designed for turn-taking prediction research.
Source
Audio corpus: CANDOR (English conversational… See the full description on the dataset page: https://huggingface.co/datasets/hiraki/candor-turntaking-annotations.turn-taking-test-v1
Turn Taking Test Dataset
This dataset is collected for turn-taking benchmarking. The original recordings consisted of long-form conversations. These recordings were first reviewed and labeled manually by human annotators. After labeling, the conversations were segmented into shorter clips, ensuring that each segment preserved the context needed for accurate interpretation while maintaining alignment with the original annotations. The metadata contains the original filename, the last… See the full description on the dataset page: https://huggingface.co/datasets/Krisp-AI/turn-taking-test-v1.turntaking-contextual-ttsturn-takingThis dataset teaches a humanoid robot
when to speak and when to listen.
Focus:
Turn-taking
Polite interaction
conversational-turn-taking-test-dataset
Conversational TTS Dataset
Turn-level conversational speech data collected from YouTube.
Sampling rate: 24kHz mono
Format: Each row is one turn in a conversation
Grouped by: conversation_id + turn_index for reconstructing conversations
Usage
from datasets import load_dataset
ds = load_dataset("somu9/conversational-tts")
turn-taking-cues-json
Turn-Taking Cues Dataset
JSON dataset describing conversational turn-taking cues
for human–robot dialogue systems.