Segmental Audio Word2Vec: Representing Utterances as Sequences of Vectors with Applications in Spoken Term Detection
Table 2: Spoken word segmentation evaluation compared to different methods across different languages. Random segmentation was also provided as a baseline.
['Lang. Method', 'English P', 'English R', 'English F1', 'CZ F1', 'FR F1', 'GE F1']
Precision (P) and recall (R) were also provided for English. We see that the proposed SSAE performed significantly better than the other two methods on all languages except comparable to GAS for German. Also, for English recall about 50% was achieved while the precision was significantly lower, which implies many of the word boundaries were actually identified, but many spoken words were in fact segmented into subword units. Similar trends were found for other languages.