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from dataclasses import dataclass |
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from enum import Enum |
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@dataclass |
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class Task: |
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benchmark: str |
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metric: str |
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col_name: str |
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class Tasks(Enum): |
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task0 = Task("tts_vocoder1", "MCD", "MCD Eval") |
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task1 = Task("tts_vocoder2", "Log F0 RMSE", "Log F0 RMSE Eval") |
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task2 = Task("tts_vocoder3", "UTMOS", "UTMOS Eval") |
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task3 = Task("tts_vocoder4", "Bitrate", "Bitrate") |
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task4 = Task("tts_vocoder5", "Sample Rate", "Sample Rate") |
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task6 = Task("tts_vocoder7", "LowSR-Rank", "LowSR-Rank") |
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TITLE = """<h1 align="center" id="space-title">Discrete-based Vocoder (LowSR) Leaderboard</h1>""" |
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INTRODUCTION_TEXT = """ |
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The leaderboard for discrete speech challenge (TTS Challenge - Vocoder Track - LowSR) at Interspeech 2024. Challenge details can be found at https://www.wavlab.org/activities/2024/Interspeech2024-Discrete-Speech-Unit-Challenge/ |
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""" |
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LLM_BENCHMARKS_TEXT = f""" |
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## How it works |
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The evaluation (static version) are conducted by the organizers only. |
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We will accept submissions from the google form (see rules in the challenge website). |
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## Reproducibility |
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To reproduce our results, please refer to the evaluation scripts at https://github.com/espnet/espnet/tree/master/egs2/TEMPLATE/tts1#evaluation |
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""" |
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EVALUATION_QUEUE_TEXT = """ |
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""" |
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CITATION_BUTTON_LABEL = "Copy the following snippet to cite these results and the challenge (coming soon, for now, please cite the challenge website)" |
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CITATION_BUTTON_TEXT = r""" |
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""" |
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