We lifted 4 functions out of this paper's own repositories and ran 1 of them in a sandbox. "Ran" means the function executed on a synthesized input and returned a value. It is not a reproduction of the paper's results.
| Repository | Role | Ran |
|---|---|---|
| fgnt/meeteval | canonical | 1 of 4 |
| Function | Status | Where it lives |
|---|---|---|
| fix_json | Ran | fgnt/meeteval/meeteval/io/chime7.py code served (permissive licence) · get_code("5ba8b304a21baea4") |
| dscore | Not yet run | fgnt/meeteval/meeteval/der/nryant_dscore.py code served (permissive licence) · get_code("23390c25947fc56d") |
| dscore_multifile | Not yet run | fgnt/meeteval/meeteval/der/nryant_dscore.py code served (permissive licence) · get_code("9343559748e3cf11") |
| get_sample_rate | Not yet run | fgnt/meeteval/meeteval/io/pbjson.py code served (permissive licence) · get_code("65a8c5e5c4c6752c") |
Some links come from the archived Papers with Code dataset (CC BY-SA 4.0): attribution and licence.
MeetEval is an open-source toolkit to evaluate all kinds of meeting transcription systems. It provides a unified interface for the computation of commonly used Word Error Rates (WERs), specifically cpWER, ORC-WER and MIMO-WER along other WER definitions. We extend the cpWER computation by a temporal constraint to ensure that only words are identified as correct when the temporal alignment is plausible. This leads to a better quality of the matching of the hypothesis string to the reference string that more closely resembles the actual transcription quality, and a system is penalized if it provides poor time annotations. Since word-level timing information is often not available, we present a way to approximate exact word-level timings from segment-level timings (e.g., a sentence) and show that the approximation leads to a similar WER as a matching with exact word-level annotations. At the same time, the time constraint leads to a speedup of the matching algorithm, which outweighs the additional overhead caused by processing the time stamps.
The same record, over MCP at https://syntology.ai/mcp:
get_harvested_code_for_paper("2307.11394")
get_code_for_paper("2307.11394")
have("2307.11394")
Connect an agent — have() is free.