datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
tool-calling-s2s-v2
Tool-calling speech-to-speech dialogues (v2)
Synthetic spoken dialogues between a visitor and the voice receptionist of a fictional company,
in French and English, with the tool calls the assistant makes between turns. Built to finetune a
speech-to-speech model (LFM2-Audio) so that it answers by voice and decides when to call a tool.
Four tools exist: find_employee, notify_employee_via_teams, call_backup_staff,
get_company_info. A dialogue is a list of turns: the visitor's… See the full description on the dataset page: https://huggingface.co/datasets/baptistefrancois1/tool-calling-s2s-v2.lfm2-tool-aware-dataset-v1
LFM2-Tool-Aware Dataset (v1)
Synthetic speech dataset for fine-tuning LFM2.5-Audio-class audio LLMs to be tool-aware: read a tool list from the system prompt, acknowledge briefly when a user query matches a listed tool, refuse politely when no tool covers the query, and otherwise behave as a normal conversational model.
Used to train matbee/lfm2.5-audio-tool-aware-v1 (96.6% accuracy on the held-out eval split).
What this teaches a model
Voice-assistant systems often… See the full description on the dataset page: https://huggingface.co/datasets/matbee/lfm2-tool-aware-dataset-v1.lfm2-tool-aware-dataset-v2
LFM2-Tool-Aware Dataset (v2)
Synthetic speech dataset for fine-tuning LFM2.5-Audio-class audio LLMs to handle both turns of a tool-augmented voice flow: acknowledge briefly on turn 1, then narrate the dispatcher's result on turn 2 after the coordinator injects it via set_context().
Used to train matbee/lfm2.5-audio-tool-aware-v2 (~97% accuracy on the eval split, including the new turn-2 narration class).
What's new in v2
The v1 dataset taught the model to ack-and-stop… See the full description on the dataset page: https://huggingface.co/datasets/matbee/lfm2-tool-aware-dataset-v2.moshi-tool-audio
Moshi Tool-Calling — Audio-Grounded Dataset
Audio-grounded data teaching Moshi / PersonaPlex to emit tool-call special
tokens in its inner monologue when it hears a request — and to stay quiet
otherwise (listening/idle frames are trained to PAD).
Each row is a code tensor codes[17, T] at 12.5 Hz:
rows
stream
content
0
text monologue
PAD while listening/idle, `<
1:9
Moshi audio
silence
9:17
user audio
the spoken question (edge-tts), Mimi-encoded
mask=1 marks… See the full description on the dataset page: https://huggingface.co/datasets/abrarfahim/moshi-tool-audio.AtlasSpeech-Dialogues
AtlasSpeech Dialogues
AtlasSpeech Dialogues contains consented conversational audio segments and aligned transcripts for robustness research.
Data fields
Each record contains an audio reference, transcript, speaker split, and recording environment tag.
Access notes
Users should retain the supplied split identifiers when reporting benchmark results.
Documentation stewardship
Dataset: toolathlonEval/AtlasSpeech-Dialogues
Standard: Open… See the full description on the dataset page: https://huggingface.co/datasets/toolathlonEval/AtlasSpeech-Dialogues.github_fetch_huggingface_pdf-tools_terminal_2096-docaudit-7c91-speech-transcripts
Speech Transcripts
Dataset Summary
Time-aligned transcripts of English speech audio.
Dataset Structure
Data fields: audio_path, text, start_time, end_time.
Licensing Information
This dataset is released under the CC BY-SA 4.0 license (cc-by-sa-4.0).