Time-compression: systems concerns, usage, and benefits

With the proliferation of online multimedia content and thepopularity of multimedia streaming systems, it is increasinglyuseful to be able to skim and browse multimedia quickly. A keytechnique that enables quick browsing of multimedia istime-compression. Prior research has described how speech can betime-compressed (shortened in duration) while preserving the pitchof the audio. However, client-server systems providing thisfunctionality have not been available. In this paper, we first describe the key tradeoffs faced bydesigners of streaming multimedia systems deployingtime-compression. The implementation tradeoffs primarily impact thegranularity of time-compression supported (discrete vs. continuous)and the latency (wait-time) experienced by users after adjustingdegree of time-compression. We report results of user studiesshowing impact of these factors on the average- compression-rateachieved. We also present data on the usage patterns and benefitsof time compression. Overall, we show significant time-savings forusers and that considerable flexibility is available to thedesigners of client-server streaming systems with timecompression.

[1]  Barry Arons,et al.  VoiceNotes: a speech interface for a hand-held voice notetaker , 1993, INTERCHI.

[2]  John B. Voor,et al.  The effect of practice upon the comprehension of time‐compressed speech , 1965 .

[3]  Anthony J. Tarquin,et al.  TIME COMPRESSION EFFECTS OF VIDEOTAPES ON STUDENTS. , 1984 .

[4]  Kevin Harrigan,et al.  The SPECIAL System: Self-Paced Education with Compressed Interactive Audio Learning , 1995 .

[5]  G. A. Miller,et al.  The Intelligibility of Interrupted Speech , 1948 .

[6]  T. Sticht,et al.  Review of research on the intelligibility and comprehension of accelerated speech. , 1969, Psychological bulletin.

[7]  Barry Arons,et al.  The audio notebook: paper and pen interaction with structured speech , 2001, CHI.

[8]  G. Fairbanks,et al.  Method for time of frequency compression-expansion of speech , 1954 .

[9]  Barry Arons,et al.  A Conversational Telephone Messaging System , 1984, IEEE Transactions on Consumer Electronics.

[10]  Paul Resnick,et al.  Skip and scan: cleaning up telephone interface , 1992, CHI '92.

[11]  Edward P. Neuburg,et al.  Simple pitch‐dependent algorithm for high‐quality speech‐rate changing , 1977 .

[12]  Daniel S. Beasley,et al.  chapter 12 – Time- and Frequency-Altered Speech , 1976 .

[13]  G W Heiman,et al.  Word intelligibility decrements and the comprehension of time-compressed speech , 1986, Perception & psychophysics.

[14]  Donald Joseph Hejna,et al.  Real-time time-scale modification of speech via the synchronized overlap-add algorithm , 1990 .

[15]  R. J. Scott.  Time adjustment in speech synthesis. , 1967, The Journal of the Acoustical Society of America.

[16]  D. B. Orr,et al.  TRAINABILITY OF LISTENING COMPREHENSION OF SPEEDED DISCOURSE. , 1965, Journal of educational psychology.

[17]  M. Portnoff,et al.  Time-scale modification of speech based on short-time Fourier analysis , 1981 .

[18]  W. D. Garvey.  The intelligibility of abbreviated speech patterns , 1953 .

[19]  Richard Mander,et al.  Working with audio: integrating personal tape recorders and desktop computers , 1992, CHI '92.

[20]  W. D. Garvey.  The intelligibility of speeded speech. , 1953, Journal of experimental psychology.

[21]  Jae S. Lim,et al.  Signal estimation from modified short-time Fourier transform , 1983, ICASSP.

[22]  N. F. Maxemchuk,et al.  An experimental speech storage and editing facility , 1980, The Bell System Technical Journal.

[23]  Barry Arons,et al.  SpeechSkimmer: a system for interactively skimming recorded speech , 1997, TCHI.

[24]  Barry Arons,et al.  Techniques, Perception, and Applications of Time-Compressed Speech , 2009 .