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"""
This file contains the text content for the leaderboard client.
"""
HEADER_MARKDOWN = """
# EMMA JSALT25 Benchmark – Multi-Talker ASR Evaluation
Welcome to the official leaderboard for benchmarking **multi-talker ASR systems**, hosted by the **EMMA JSALT25 team**.
"""
LEADERBOARD_TAB_TITLE_MARKDOWN = """
## Leaderboard
Below you’ll find the latest results submitted to the benchmark. Models are evaluated using **`meeteval`** with **TCP-WER [%] (collar=5s)**.
For AISHELL-4 and AliMeeting conversion to simplified Mandarin is applied, and tcpCER [%] is used.
"""
SUBMISSION_TAB_TITLE_MARKDOWN = """
## Submit Your Model
To submit your MT-ASR hypothesis to the benchmark, complete the form below:
- **Submitted by**: Your name or team identifier.
- **Model ID**: A unique identifier for your submission (used to track models on the leaderboard).
- **Hypothesis File**: Upload a **SegLST `.json` file** that includes **all segments across datasets** in a single list.
- **Task**: Choose the evaluation task (e.g., single-channel ground-truth diarization).
- **Datasets**: Select one or more datasets you wish to evaluate on.
📩 To enable submission, please [email the EMMA team](mailto:ipoloka@fit.vut.cz) to receive a **submission token**.
After clicking **Submit**, your model will be evaluated and results displayed in the leaderboard.
"""
ADDITIONAL_NOTES_MARKDOWN = """
### Reference/Hypothesis File Format
🛠️ Reference annotations were constructed via the `prepare_gt.sh` script. To add a new dataset, please create a pull request modifying `prepare_gt.sh`.
📚 For details about SegLST format, please see the [SegLST documentation in MeetEval](https://github.com/fgnt/meeteval?tab=readme-ov-file#segment-wise-long-form-speech-transcription-annotation-seglst).
🔄 By default, **Chime-8 normalization** is applied during evaluation for both references and hypotheses.
You can choose to disable this using the checkbox above.
"""
LEADERBOARD_CSS = """
#leaderboard-table th .header-content {
white-space: nowrap;
}
""" |