We lifted 10 functions out of this paper's own repositories and ran 10 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/sed_scores_eval | canonical | 10 of 10 |
| Function | Status | Where it lives |
|---|---|---|
| confidence_interval | Ran | fgnt/sed_scores_eval/sed_scores_eval/base_modules/bootstrap.py code served (permissive licence) · get_code("e3b7b971e1627f6e") |
| create_score_dataframe | Ran | fgnt/sed_scores_eval/sed_scores_eval/base_modules/scores.py code served (permissive licence) · get_code("abc0fd38db1a63cd") |
| event_counts_and_durations | Ran | fgnt/sed_scores_eval/sed_scores_eval/base_modules/ground_truth.py code served (permissive licence) · get_code("f68a9049b45e1f45") |
| fscore_from_precision_recall | Ran | fgnt/sed_scores_eval/sed_scores_eval/base_modules/precision_recall.py code served (permissive licence) · get_code("c8a897b47e7b4f4d") |
| get_unique_thresholds | Ran | fgnt/sed_scores_eval/sed_scores_eval/base_modules/scores.py code served (permissive licence) · get_code("aad12409c949295f") |
| multi_label_to_single_label_ground_truths | Ran | fgnt/sed_scores_eval/sed_scores_eval/base_modules/ground_truth.py code served (permissive licence) · get_code("06db155feca2d5ac") |
| onset_deltas | Ran | fgnt/sed_scores_eval/sed_scores_eval/base_modules/detection.py code served (permissive licence) · get_code("398f113c618ff50e") |
| onset_offset_curves | Ran | fgnt/sed_scores_eval/sed_scores_eval/base_modules/detection.py code served (permissive licence) · get_code("788278d91b11722f") |
| parse_ground_truth | Ran | fgnt/sed_scores_eval/sed_scores_eval/base_modules/io.py code served (permissive licence) · get_code("10bfd6b3a4aa8961") |
| validate_score_dataframe | Ran | fgnt/sed_scores_eval/sed_scores_eval/base_modules/scores.py code served (permissive licence) · get_code("4192ece3e059f9d5") |
Some links come from the archived Papers with Code dataset (CC BY-SA 4.0): attribution and licence.
Performing an adequate evaluation of sound event detection (SED) systems is far from trivial and is still subject to ongoing research. The recently proposed polyphonic sound detection (PSD)-receiver operating characteristic (ROC) and PSD score (PSDS) make an important step into the direction of an evaluation of SED systems which is independent from a certain decision threshold. This allows to obtain a more complete picture of the overall system behavior which is less biased by threshold tuning. Yet, the PSD-ROC is currently only approximated using a finite set of thresholds. The choice of the thresholds used in approximation, however, can have a severe impact on the resulting PSDS. In this paper we propose a method which allows for computing system performance on an evaluation set for all possible thresholds jointly, enabling accurate computation not only of the PSD-ROC and PSDS but also of other collar-based and intersection-based performance curves. It further allows to select the threshold which best fulfills the requirements of a given application. Source code is publicly available in our SED evaluation package sed_scores_eval.
The same record, over MCP at https://syntology.ai/mcp:
get_harvested_code_for_paper("2201.13148")
get_code_for_paper("2201.13148")
have("2201.13148")
Connect an agent — have() is free.