Speaker Count Estimation Via Similarity Analysis

via “speaker-count-estimation-and-model-selection”

automatic-speech-recognition model by undefined. 1,02,76,778 downloads.

Unique: Uses embedding-space clustering quality metrics (silhouette analysis) to infer speaker count rather than relying on external classifiers. Integrates with the diarization pipeline to enable automatic parameter tuning.

vs others: Provides speaker count estimation as a built-in capability rather than requiring separate tools or manual inspection. More accurate than energy-based or spectral-based speaker count estimation methods.

via “speaker-count-estimation-via-similarity-analysis”

automatic-speech-recognition model by undefined. 27,65,322 downloads.

Unique: Combines multiple statistical heuristics (gap statistic, silhouette analysis, knee-point detection) and uses ensemble voting to estimate speaker count, improving robustness vs. single-method approaches. Produces confidence scores based on agreement between heuristics.

vs others: More robust than fixed-k clustering; automatic speaker count detection vs. manual specification; ensemble approach reduces sensitivity to individual heuristic failures.