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Story Segmentation in English Mandarin and Arabic Broadcast News. Andrew Rosenberg, Julia Hirschberg Columbia University 5/31/06. Outline. Introduction Approach Motivating Example Results. Why do we need story segmentation?. News shows commonly contain many distinct stories.

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story segmentation in english mandarin and arabic broadcast news

Story Segmentation in English Mandarin and Arabic Broadcast News

Andrew Rosenberg, Julia Hirschberg

Columbia University

5/31/06

outline
Outline
  • Introduction
  • Approach
  • Motivating Example
  • Results

HLT/NAACL'06 - Practice Talk

why do we need story segmentation
Why do we need story segmentation?
  • News shows commonly contain many distinct stories.
  • Identifying story (topic) boundaries improves:
    • Summarization [Hearst and Plaunt 93]
    • Information Retrieval [Hearst and Plaunt 93]
    • Anaphora Resolution [Kozima 93]

HLT/NAACL'06 - Practice Talk

our approach
Our Approach
  • Input: Speech signal, ASR transcript, automatic speaker diarization and automatic sentence boundary hypotheses
  • Assume: story boundaries occur at sentence boundaries
  • JRip: java implementation of Cohen’s RIPPER, a rule induction algorithm.
    • build rulesets for each show individually
    • using Lexical, Acoustic and Speaker-dependant features.

HLT/NAACL'06 - Practice Talk

corpus description
Corpus Description
  • Broadcast News material from TDT4 Corpus distributed by LDC
    • English: 312.5 hrs, 450 broadcasts 6 shows
    • Mandarin: 134 hrs, 205 broadcasts, 3 shows
    • Arabic: 88.5 hrs, 109 broadcasts, 2 shows
  • Each broadcast contains between 10 and 20 stories

HLT/NAACL'06 - Practice Talk

story segmentation example
Story segmentation example

the united states finished at the top with a total of ninety seven medals thirty nine of them gold russian china and australia rounded up its four andrea run economy seemed to champion style welcome home even though she was stripped of her individual gold medal at the sydney olympics in armenian gymnast tested positive for a banned stimulant that was in a nonprescription cold medicine she took from any as government is honoring her with its own gold medal inscribed everlasting olympic champion the international olympic committee did allow run a con to keep her team gold medal and the silver medal she won in the vote compass a spokeswoman says republican senator strom thurmond is going very well after falling ill saturday he spent the night it will to read army medical center in washington

HLT/NAACL'06 - Practice Talk

story segmentation example7
Story segmentation example
  • the united states finished at the top with a total of ninety seven medals thirty nine of them gold russian china and australia rounded up its four
  • andrea run economy seemed to champion style welcome home even though she was stripped of her individual gold medal at the sydney olympics in armenian gymnast tested positive for a banned stimulant
  • that was in a nonprescription cold medicine she took from any as government is honoring her with its own gold medal inscribed everlasting olympic champion
  • the international olympic committee did allow run a con to keep her team gold medal and the silver medal she won in the vote compass a spokeswoman says republican senator strom thurmond is doing very well after falling ill saturday
  • he spent the night it will to read army medical center in washington

HLT/NAACL'06 - Practice Talk

story segmentation example8
Story segmentation example
  • the united states finished at the top with a total of ninety seven medals thirty nine of them gold russian china and australia rounded up its four
  • andrea run economy seemed to champion style welcome home even though she was stripped of her individual gold medal at the sydney olympics ***in armenian gymnast tested positive for a banned stimulant
  • --- that was in a nonprescription cold medicine she took from any as government is honoring her with its own gold medal inscribed everlasting olympic champion
  • the international olympic committee did allow run a con to keep her team gold medal and the silver medal she won in the vote compass*** a spokeswoman says republican senator strom thurmond is doing very well after falling ill saturday
  • he spent the night it will to read army medical center in washington

HLT/NAACL'06 - Practice Talk

story segmentation example9
Story segmentation example
  • the united states finished at the top with a total of ninety seven medals thirty nine of them gold russian china and australia rounded up its four
  • andrea run economy seemed to champion style welcome home even though she was stripped of her individual gold medal at the sydney olympics in armenian gymnast tested positive for a banned stimulant
  • that was in a nonprescription cold medicine she took from any as government is honoring her with its own gold medal inscribed everlasting olympic champion
  • the international olympic committee did allow run a con to keep her team gold medal and the silver medal she won in the vote compass a spokeswoman says republican senator strom thurmond is doing very well after falling ill saturday
  • he spent the night it will to read army medical center in washington

HLT/NAACL'06 - Practice Talk

lexical features
Lexical Features
  • TextTiling
    • Identify boundaries with locally minimal cosine similarity of the preceding and following regions.
  • LCSeg
    • Augments the above process by weighting cosine similarity by a lexical chain score: a measure of lexical repetition.
  • ‘Cue’ Unigrams
    • Those (stemmed, when available) unigrams that are significantly more likely to appear near the start or end of a story.

HLT/NAACL'06 - Practice Talk

acoustic features
Acoustic Features
  • Pitch and Intensity
    • Min, max, median, mean, std.dev., mean absolute slope
    • Calculated over previous sentence, and first-order difference between previous and following
  • Vowel Duration
    • Mean vowel length, sentence final vowel length, sentence final rhyme length
  • Voiced/Total 10ms frames as an approximation of speaking rate

HLT/NAACL'06 - Practice Talk

speaker dependent features
Speaker-dependent Features
  • Based on automatic speaker diarization
    • Performed by our collaborators at U.Washington
  • Normalization of acoustic features.
  • Speaker participation features as a rough approximation of speaker “role”.
    • What percent of the show’s sentences does the speaker of the previous sentence deliver?
    • First turn? Last turn?
    • Is this the first speaker in the show?

HLT/NAACL'06 - Practice Talk

ruleset excerpts
Ruleset Excerpts
  • (ENG)If (speaker_distribution > .16) and (length > 15.85) and (maxI > 80.5) and (minI < 43.6) and (vowels_per_sec < 3) Then SEGMENT
  • (MAN)If (speaker_boundary) and (last_speaker_turn) and (speaker_distribution > 0.036) and (vowels_per_sec_norm > 1.03) Then SEGMENT
  • (ARB)If (following_cue_words > 1) and (preceding_cue_words > 1) and (meanI < 67.8) and (stdev_I > 8.0) Then SEGMENT

HLT/NAACL'06 - Practice Talk

results english
Results - English

HLT/NAACL'06 - Practice Talk

results mandarin
Results - Mandarin

HLT/NAACL'06 - Practice Talk

results arabic
Results - Arabic

HLT/NAACL'06 - Practice Talk

conclusions
Conclusions
  • The described approach is successful at detecting story boundaries in English and Mandarin BN, though recall could be improved.
  • The acoustic features shown here and elsewhere to be indicative of topic shifts are not discriminative on Arabic BN.
    • Arabic has a different intonation strategy
    • MSA is not any speaker’s native language
    • Errors from previous processing -- ASR, sentence segmentation -- hinder the effectiveness of acoustic analysis.

HLT/NAACL'06 - Practice Talk

thank you

Thank You

{amaxwell,julia}@columbia.edu