---
dataset_info:
  features:
  - name: segment_id
    dtype: string
  - name: transcription
    dtype: string
  - name: label
    dtype: string
  - name: tempo
    dtype: int64
  - name: note_midi
    sequence: float64
  - name: note_phns
    sequence: string
  - name: note_lyrics
    sequence: string
  - name: note_start_times
    sequence: float64
  - name: note_end_times
    sequence: float64
  - name: phns
    sequence: string
  - name: phn_start_times
    sequence: float64
  - name: phn_end_times
    sequence: float64
  - name: note_midi_length
    dtype: int64
  - name: lyric_word_length
    dtype: int64
  splits:
  - name: train
    num_bytes: 1092803
    num_examples: 833
  download_size: 347719
  dataset_size: 1092803
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
task_categories:
- text-to-audio
license: cc-by-nc-nd-4.0
---

# SingingSDS Dataset

This repository contains the dataset for **SingingSDS: A Singing-Capable Spoken Dialogue System for Conversational Roleplay Applications**.

SingingSDS is an innovative role-playing singing dialogue system that seamlessly converts natural speech input into character-based singing output. It integrates automatic speech recognition (ASR), large language models (LLM), and singing voice synthesis (SVS) to create immersive conversational singing experiences. This dataset provides structured annotations, including segment ID, transcription, labels, tempo, MIDI notes, phonemes, lyrics, and their timing information, which are crucial for training and evaluating the SVS components of the SingingSDS system.

*   **Paper**: [SingingSDS: A Singing-Capable Spoken Dialogue System for Conversational Roleplay Applications](https://huggingface.co/papers/2511.20972)
*   **Code**: [https://github.com/SingingSDS/SingingSDS](https://github.com/SingingSDS/SingingSDS)
*   **Demo Space**: [https://huggingface.co/spaces/espnet/SingingSDS](https://huggingface.co/spaces/espnet/SingingSDS)

## Sample Usage (SingingSDS System)

The following examples demonstrate how to use the SingingSDS system via its Command Line Interface (CLI). This showcases how models trained with datasets like this can be applied for inference.

### Example Usage

```bash
python cli.py \
  --query_audio tests/audio/hello.wav \
  --config_path config/cli/yaoyin_default.yaml \
  --output_audio outputs/yaoyin_hello.wav \
  --eval_results_csv outputs/yaoyin_test.csv
```

### Inference-Only Mode

Run minimal inference without evaluation.

```bash
python cli.py \
  --query_audio tests/audio/hello.wav \
  --config_path config/cli/yaoyin_default_infer_only.yaml \
  --output_audio outputs/yaoyin_hello.wav
```

### Parameter Description

*   `--query_audio`: Input audio file path (required)
*   `--config_path`: Configuration file path (default: `config/cli/yaoyin_default.yaml`)
*   `--output_audio`: Output audio file path (required)
*   `--eval_results_csv`: Output CSV file path for evaluation results (optional, used in example usage)