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VoiceMOS Challenge 2024 - Speech Quality Assessment

Speech quality assessment using Mean Opinion Score (MOS). Annotators rate synthesized or processed speech on naturalness, intelligibility, and overall quality on 1-5 scales (Huang et al., IEEE SLT 2024).

1:42Classify this audio:HappySadAngryNeutralSubmit

Configuration Fileconfig.yaml

This Potato config reproduces the annotation task. Save it as config.yaml and run potato start config.yaml to try it.

yaml
# VoiceMOS Challenge 2024 - Speech Quality Assessment
# Based on Huang et al., IEEE SLT 2024
# Paper: https://arxiv.org/abs/2409.07001
# Dataset: https://sites.google.com/view/voicemos-challenge/home
#
# Task: Rate synthesized/processed speech quality using Mean Opinion Score (MOS).
# Evaluate naturalness, intelligibility, and overall quality on 1-5 scales.
#
# Guidelines:
# - Listen to each clip fully before rating
# - Rate naturalness: How close to natural human speech?
# - Rate intelligibility: How easy is it to understand the words?
# - Rate overall quality: General impression of the speech quality
# - Use the full 1-5 scale; avoid always rating in the middle

annotation_task_name: "VoiceMOS Challenge 2024: Speech Quality Assessment"
task_dir: "."

data_files:
  - sample-data.json
item_properties:
  id_key: "id"
  text_key: "audio_url"

output_annotation_dir: "annotation_output/"
output_annotation_format: "json"

annotation_schemes:
  - annotation_type: likert
    name: naturalness
    description: "How natural does the speech sound? (1 = Very unnatural, 5 = Completely natural)"
    size: 5
    min_label: "Very unnatural"
    max_label: "Completely natural"
    labels:
      - "1 - Very unnatural"
      - "2 - Somewhat unnatural"
      - "3 - Moderately natural"
      - "4 - Mostly natural"
      - "5 - Completely natural"

  - annotation_type: likert
    name: intelligibility
    description: "How easy is it to understand the speech? (1 = Unintelligible, 5 = Perfectly clear)"
    size: 5
    min_label: "Unintelligible"
    max_label: "Perfectly clear"
    labels:
      - "1 - Unintelligible"
      - "2 - Mostly unintelligible"
      - "3 - Somewhat intelligible"
      - "4 - Mostly intelligible"
      - "5 - Perfectly clear"

  - annotation_type: likert
    name: overall_quality
    description: "What is the overall quality of this speech? (1 = Bad, 5 = Excellent)"
    size: 5
    min_label: "Bad"
    max_label: "Excellent"
    labels:
      - "1 - Bad"
      - "2 - Poor"
      - "3 - Fair"
      - "4 - Good"
      - "5 - Excellent"

audio_display:
  show_waveform: true
  playback_controls: true
  allow_speed_control: true

allow_all_users: true
instances_per_annotator: 200
annotation_per_instance: 5
allow_skip: true
skip_reason_required: false

Sample Datasample-data.json

json
[
  {
    "id": "voicemos_001",
    "audio_url": "https://example.com/audio/voicemos/tts_system_a_001.wav",
    "system_id": "system_a",
    "duration": 4.2,
    "text_content": "The weather forecast for tomorrow predicts clear skies and mild temperatures."
  },
  {
    "id": "voicemos_002",
    "audio_url": "https://example.com/audio/voicemos/tts_system_b_001.wav",
    "system_id": "system_b",
    "duration": 3.8,
    "text_content": "Please remember to submit your report by the end of the business day."
  }
]

// ... and 8 more items

Get This Design

View on GitHub

Clone or download from the repository

Quick start:

git clone https://github.com/davidjurgens/potato-showcase.git
cd potato-showcase/audio/voicemos-quality-assessment
potato start config.yaml

Dataset & paper

Huang et al., IEEE SLT 2024

Citation (BibTeX)

bibtex
@inproceedings{huang2024voicemos,
    title = "The {V}oice{MOS} Challenge 2024: Beyond Speech Quality Prediction",
    author = "Huang, Wen-Chin and Fu, Szu-Wei and Cooper, Erica and Zezario, Ryandhimas E. and Toda, Tomoki and Wang, Hsin-Min and Yamagishi, Junichi and Tsao, Yu",
    booktitle = "2024 IEEE Spoken Language Technology Workshop (SLT)",
    year = "2024",
    pages = "803--810",
    publisher = "IEEE",
    doi = "10.1109/SLT61566.2024.10832295",
    url = "https://arxiv.org/abs/2409.07001"
}

Details

Annotation Types

likert

Domain

Speech ProcessingQuality Assessment

Use Cases

Speech Quality RatingTTS EvaluationVoice Synthesis Assessment

Tags

audiospeech-qualitymosttsvoice-synthesisinterspeech2024

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