Corpus-Independent History Compression for Stochastic Turn-Taking Models

Stochastic turn-taking models use a truncated representation of past

speech activity to specify how likely a speaker is to talk at the next

instant. An unanswered question in such modeling is how far back

to extend the conditioning context. We study this question using

Switchboard (English, telephone) and Spontal (Swedish, face-toface)

conversations. We also explore whether to trade off precision

with range when moving backward in the history. We find that

(1) a nearly logarithmic compression of history is optimal, for both

speaker and interlocutor; (2) the absolute duration of the conditioning

context is at least 7 seconds; and (3) the compression scheme

generalizes remarkably well across the two different corpora.

icassp2012-turnmodel-history-compression.pdf
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Publisher  IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

Details

TypeInproceedings
Pages4937 - 4940
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