Datasets:

Shadow0482
/

maya-tts

license: cc-by-4.0
task_categories:
  - text-to-speech
language:
  - en
tags:
  - speech
  - audio
  - tts
  - voice-cloning
  - fish-speech
  - synthetic
  - maya-tts
size_categories:
  - 1K<n<10K
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*

Maya TTS (maya-tts)

A high-fidelity expressive synthetic speech dataset for Maya, built using Qwen2.5-1.5B-Instruct for conversational dialogues and Fish Audio S1-mini for zero-shot voice cloning.

Dataset Overview

Total Clips: 1518
Total Duration: 1.451 hours (87.07 minutes)
Audio Format: WAV (embedded directly into Parquet shards via Hugging Face Audio feature)
Sampling Rate: 44100 Hz
Language: English (en)

Features

Column	Type	Description
`id`	`string`	Unique zero-padded utterance identifier
`audio`	`Audio`	Embedded audio sample and decoding dict
`text`	`string`	Transcribed dialogue spoken by the cloned voice
`emotion`	`string`	Primary target emotion label (e.g. `happy`, `anxious`, `excited`)
`tag`	`string`	Specific delivery tone/special acoustic style (e.g. `whispering`, `shouting`)
`language`	`string`	Language code (`en`)
`duration`	`float`	Clip length in seconds

Reference Speaker Information

Target Voice: Cloned from single reference prompt (ref_voice.wav).
Reference Voice Transcript: "The fog had settled deep over the harbor long before midnight, turning the distant stone towers into jagged gray silhouettes against the sea. Out on the water, every sound carried double its daytime weight, the dull slap of cold black tide against the wooden pilings, the scrape of rusted iron chains, and the slow whistle of the gale driving through the cliffside pines. There is a particular stillness"

Distribution & Statistics

Top Emotions

Emotion	Count
`satisfied`	45
`worried`	39
`scared`	39
`painful`	38
`sad`	38
`disdainful`	38
`surprised`	38
`delighted`	37
`sincere`	37
`angry`	37

Delivery Styles & Tone Tags

Tag	Count
`sobbing`	41
`laughing`	39
`sighing`	38
`chuckling`	35
`in a hurry tone`	35
`soft tone`	34
`screaming`	34
`whispering`	32
`crying loudly`	29
`shouting`	27

Usage

from datasets import load_dataset

# Load directly as an iterable audio stream
dataset = load_dataset("Shadow0482/maya-tts", split="train", streaming=True)

for sample in dataset.take(2):
    print(sample["id"], sample["text"])
    audio_array = sample["audio"]["array"]
    sample_rate = sample["audio"]["sampling_rate"]

Generation Pipeline

Script Generation: Prompted Qwen/Qwen2.5-1.5B-Instruct across multiple topics and affective directions.
Acoustic Synthesis: Zero-shot target voice cloning via fishaudio/openaudio-s1-mini.
Validation: Automatic duration, volume, and transcript alignment filtering.