Publications by Mike Lincoln
mlincol1.bib
@inproceedings{zwyssig2010,
author = {Zwyssig, Erich and Lincoln, Mike and Renals, Steve},
title = {A Digital Microphone Array for Distant Speech
Recognition},
booktitle = {Proc. IEEE ICASSP--10},
pages = {5106--5109},
abstract = {In this paper, the design, implementation and testing
of a digital microphone array is presented. The array
uses digital MEMS microphones which integrate the
microphone, amplifier and analogue to digital converter
on a single chip in place of the analogue microphones
and external audio interfaces currently used. The
device has the potential to be smaller, cheaper and
more flexible than typical analogue arrays, however the
effect on speech recognition performance of using
digital microphones is as yet unknown. In order to
evaluate the effect, an analogue array and the new
digital array are used to simultaneously record test
data for a speech recognition experiment. Initial
results employing no adaptation show that performance
using the digital array is significantly worse (14\%
absolute WER) than the analogue device. Subsequent
experiments using MLLR and CMLLR channel adaptation
reduce this gap, and employing MLLR for both channel
and speaker adaptation reduces the difference between
the arrays to 4.5\% absolute WER.},
doi = {10.1109/ICASSP.2010.5495040},
pdf = {http://www.cstr.inf.ed.ac.uk/downloads/publications/2010/zwyssig-icassp10.pdf},
year = 2010
}
@inproceedings{Ban00,
author = {Bangham, J.A. and Cox, S.J. and Lincoln, M. and
Marshall, I. and Tutt, M. and Wells, M},
title = {Signing for the deaf using virtual humans},
booktitle = {IEE Colloquium on Speech and Language processing for
Disabled and Elderly},
abstract = {Research at Televirtual (Norwich) and the University
of East Anglia, funded predominantly by the Independent
Television Commission and more recently by the UK Post
Office also, has investigated the feasibility of using
virtual signing as a communication medium for
presenting information to the Deaf. We describe and
demonstrate the underlying virtual signer technology,
and discuss the language processing techniques and
discourse models which have been investigated for
information communication in a transaction application
in Post Offices, and for presentation of more general
textual material in texts such as subtitles
accompanying television programmes.},
categories = {visicast,sign language,translation,UEA},
pdf = {http://www.cstr.inf.ed.ac.uk/downloads/publications/2000/iee2000-04PaperAFinal.pdf},
year = 2000
}
@article{Wray04-LC04,
author = {Wray, A. and Cox, S.J. and Lincoln, M. and Tryggvason,
J.},
title = {A Formulaic Approach to Translation at the Post
Office: Reading the Signs},
journal = {Language and Communication},
volume = {24},
number = {1},
pages = {59-75},
abstract = {TESSA is an interactive translation system designed to
support transactions between a post office clerk and a
deaf customer. The system translates the clerk's speech
into British Sign Language (BSL), displayed on a
screen, using a specially-developed avatar (virtual
human). TESSA is a context-constrained exemplification
of one of two basic approaches to machine translation,
neither of which can currently fulfil all of the
demands of successful automatic translation. Drawing on
recent research in theoretical psycholinguistics, we
show how TESSA is a convincing prototype model of one
aspect of real human language processing. Ways are
suggested of exploiting this parallel, potentially
offering new possibilities for the future design of
artificial language systems.},
categories = {visicast,sign language,translation,UEA},
pdf = {http://www.cstr.inf.ed.ac.uk/downloads/publications/2004/WrayCoxetal2004.pdf},
year = 2004
}
@phdthesis{LIN99-phd,
author = {Lincoln, M.},
title = {Characterization of Speakers for Improved Automatic
Speech Recognition},
school = {University of East Anglia},
abstract = {Automatic speech recognition technology is becoming
increasingly widespread in many applications. For
dictation tasks, where a single talker is to use the
system for long periods of time, the high recognition
accuracies obtained are in part due to the user
performing a lengthy enrolment procedure to tune the
parameters of the recogniser to their particular voice
characteristics and speaking style. Interactive speech
systems, where the speaker is using the system for only
a short period of time (for example to obtain
information) do not have the luxury of long enrolments
and have to adapt rapidly to new speakers and speaking
styles. This thesis discusses the variations between
speakers and speaking styles which result in decreased
recognition performance when there is a mismatch
between the talker and the systems models. An
unsupervised method to rapidly identify and normalise
differences in vocal tract length is presented and
shown to give improvements in recognition accuracy for
little computational overhead. Two unsupervised methods
of identifying speakers with similar speaking styles
are also presented. The first, a data-driven technique,
is shown to accurately classify British and American
accented speech, and is also used to improve
recognition accuracy by clustering groups of similar
talkers. The second uses the phonotactic information
available within pronunciation dictionaries to model
British and American accented speech. This model is
then used to rapidly and accurately classify speakers.},
categories = {adaptation, ASR, speaker characteristics, BT, UEA},
pdf = {http://www.cstr.inf.ed.ac.uk/downloads/publications/1999/thesis.pdf},
year = 1999
}
@inproceedings{NistevalAMI06,
author = {T. Hain and L. Burget and L. Burget and J. dines and
G. Garau and M. Karafiat and M. Lincoln and J. Vepa and
V. Wan},
title = {The {AMI} Meeting Transcription System: Progress and
Performance},
booktitle = {Proceedings of the Rich Transcription 2006 Spring
Meeting Recognition Evaluation},
abstract = {We present the AMI 2006 system for the transcription
of speech in meetings. The system was jointly developed
by multiple sites on the basis of the 2005 system for
participation in the NIST RT'05 evaluations. The paper
describes major developments such as improvements in
automatic segmentation, cross-domain model adaptation,
inclusion of MLP based features, improvements in
decoding, language modelling and vocal tract length
normalisation, the use of a new decoder, and a new
system architecture. This is followed by a
comprehensive description of the final system and its
performance in the NIST RT'06s evaluations. In
comparison to the previous year word error rate results
on the individual headset microphone task were reduced
by 20\% relative.},
categories = {LVCSR, NIST Meeting Transcription Evaluation RT06S},
pdf = {http://www.cstr.inf.ed.ac.uk/downloads/publications/2006/AMIasr.nist06.pdf},
year = 2006
}
@inproceedings{Lin97,
author = {Lincoln, M. and Cox, S.J. and Ringland, S.},
title = {A fast method of speaker normalisation using formant
estimation},
booktitle = {5th European Conference on Speech Communication and
Technology},
pages = {2095--2098},
address = {Rhodes},
abstract = {It has recently been shown that normalisation of vocal
tract length can significantly increase recognition
accuracy in speaker independent automatic speech
recognition systems. An inherent difficulty with this
technique is in automatically estimating the
normalisation parameter from a new speaker's speech and
previous techniques have typically relied on an
exhaustive search to estimate this parameter. In this
paper, we present a method of normalising utterances by
a linear warping of the mel filter bank channels in
which in which the normalisation parameter is estimated
by fitting formant estimates to a probabilistic model.
This method is fast, computitionally inexpensive and
requires only a limited amount of data for estimation.
It generates normalisations which are close to those
which would be found by an exhaustive search. The
normalisation is applied to a phoneme recognition task
using the TIMIT database and results show a useful
improvement over an un-normalised speaker independent
system.},
categories = {adaptation, vocal tract, speaker characteristics, BT,
UEA},
pdf = {http://www.cstr.inf.ed.ac.uk/downloads/publications/1997/lincoln-espeech-97.pdf},
year = 1997
}
@inproceedings{Cox02d,
author = {Cox, S.J. and Lincoln, M. and Tryggvason, J and
Nakisa, M and Wells, Mand Tutt, M. and Abbott, S},
title = {{TESSA}, a system to aid communication with deaf
people},
booktitle = {ASSETS 2002, Fifth International {ACM SIGCAPH}
Conference on Assistive Technologies},
pages = {205-212},
address = {Edinburgh, Scotland},
abstract = {{TESSA} is an experimental system that aims to aid
transactions between a deaf person and a clerk in a
Post Office by translating the clerks speech to sign
language. A speech recogniser recognises speech from
the clerk and the system then synthesizes the
appropriate sequence of signs in British Sign language
(BSL) using a speciallydeveloped avatar. By using a
phrase lookup approach to language translation, which
is appropriate for the highly constrained discourse in
a Post Office, we were able to build a working system
that we could evaluate. We summarise the results of
this evaluation (undertaken by deaf users and Post
office clerks), and discuss how the findings from the
evaluation are being used in the development of an
improved system},
categories = {visicast,sign language,translation,UEA},
pdf = {http://www.cstr.inf.ed.ac.uk/downloads/publications/2002/Cox-Assets-2000.pdf},
year = 2002
}
@inproceedings{NistevalAMI05,
author = {T. Hain and L. Burget and J. Dines and G. Garau and M.
Karafiat and M. Lincoln and I. McCowan and D. Moore and
V. Wan and R. Ordelman and S. Renals},
title = {The 2005 {AMI} System for the transcription of Speech
in Meetings},
booktitle = {Proceedings of the Rich Transcription 2005 Spring
Meeting Recognition Evaluation},
abstract = {In this paper we describe the 2005 AMI system for the
transcription of speech in meetings used in the 2005
NIST RT evaluations. The system was designed for
participation in the speech to text part of the
evaluations, in particular for transcription of speech
recorded with multiple distant microphones and
independent headset microphones. System performance was
tested on both conference room and lecture style
meetings. Although input sources are processed using
different frontends, the recognition process is based
on a unified system architecture. The system operates
in multiple passes and makes use of state of the art
technologies such as discriminative training, vocal
tract length normalisation, heteroscedastic linear
discriminant analysis, speaker adaptation with maximum
likelihood linear regression and minimum word error
rate decoding. In this paper we describe the system
performance on the official development and test sets
for the NIST RT05s evaluations. The system was jointly
developed in less than 10 months by a multi-site team
and was shown to achieve competitive performance.},
categories = {LVCSR, NIST Meeting Transcription Evaluation RT05S},
pdf = {http://www.cstr.inf.ed.ac.uk/downloads/publications/2005/AMIasr.nist2005.pdf},
year = 2005
}
@inproceedings{Lin98,
author = {Lincoln, M. and Cox, S.J. and Ringland, S.},
title = {A Comparison of Two Unsupervised Approaches to Accent
Identification},
booktitle = {Int. Conf. on Spoken Language Processing},
pages = {109-112},
address = {Sydney},
abstract = {The ability to automatically identify a speaker's
accent would be very useful for a speech recognition
system as it would enable the system to use both a
pronunciation dictionary and speech models speci c to
the accent, techniques which have been shown to improve
accuracy. Here, we describe some experiments in
unsupervised accent classi cation. Two techniques have
been investigated to classify British- and
Americanaccented speech: an acoustic approach, in which
we analyse the pattern of usage of the distributions in
the recogniser by a speaker to decide on his most
probable accent, and a high-level approach in which we
use a phonotactic model for classi cation of the
accent. Results show that both techniques give
excellent performance on this task which is maintained
when testing is done on data from an independent
dataset.},
categories = {accent identification, speaker characteristics, BT,
UEA},
pdf = {http://www.cstr.inf.ed.ac.uk/downloads/publications/1998/lincoln-icslp-98.pdf},
year = 1998
}
@inproceedings{zwyssig2012determining,
author = {Zwyssig, E. and Renals, S. and Lincoln, M.},
title = {Determining the number of speakers in a meeting using
microphone array features},
booktitle = {Acoustics, Speech and Signal Processing (ICASSP), 2012
IEEE International Conference on},
pages = {4765--4768},
year = 2012
}
@inproceedings{zwyssig2012effect,
author = {Zwyssig, E. and Renals, S. and Lincoln, M.},
title = {{On the effect of SNR and superdirective beamforming
in speaker diarisation in meetings}},
booktitle = {Acoustics, Speech and Signal Processing (ICASSP), 2012
IEEE International Conference on},
pages = {4177--4180},
year = 2012
}
@inproceedings{jyamagis:emime,
author = {Junichi Yamagishi and Mike Lincoln and Simon King and
John Dines and Matthew Gibson and Jilei Tian and Yong
Guan},
title = {Analysis of Unsupervised and Noise-Robust
Speaker-Adaptive {HMM}-Based Speech Synthesis Systems
toward a Unified {ASR} and {TTS} Framework},
booktitle = {Proc. Interspeech 2009},
address = {Edinburgh, U.K.},
abstract = {For the 2009 Blizzard Challenge we have built an
unsupervised version of the HTS-2008 speaker-adaptive
HMM-based speech synthesis system for English, and a
noise robust version of the systems for Mandarin. They
are designed from a multidisciplinary application point
of view in that we attempt to integrate the components
of the TTS system with other technologies such as ASR.
All the average voice models are trained exclusively
from recognized, publicly available, ASR databases.
Multi-pass LVCSR and confidence scores calculated from
confusion network are used for the unsupervised
systems, and noisy data recorded in cars or public
spaces is used for the noise robust system. We believe
the developed systems form solid benchmarks and provide
good connections to ASR fields. This paper describes
the development of the systems and reports the results
and analysis of their evaluation.},
month = sep,
year = 2009
}
@article{Cox-ijhci03,
author = {Cox, S.J. and Lincoln, M. and Nakisa, M. and Wells, M.
and Tutt, M. and Abbott, S.},
title = {The Development and Evaluation of a Speech to Sign
Translation System to Assist Transactions},
journal = {Int. Journal of Human Computer Interaction},
volume = {16},
number = {2},
pages = {141-161},
abstract = {The design, development, and evaluation of an
experimental translation system that aims to aid
transactions between a deaf person and a clerk in a
post office (PO) is described. The system uses a speech
recognizer to recognize speech from a PO clerk and then
synthesizes recognized phrases in British Sign language
(BSL) using a specially developed avatar. The main
objective in developing this prototype system was to
determine how useful it would be to a customer whose
first language was BSL, and to discover what areas of
the system required more research and development to
make it more effective. The system was evaluated by 6
prelingually profoundly deaf people and 3 PO clerks.
Deaf users and PO clerks were supportive of the system,
but the former group required a higher quality of
signing from the avatar and the latter a system that
was less constrained in the phrases it could recognize;
both these areas are being addressed in the next phase
of development.},
categories = {visicast,sign language,translation,UEA},
pdf = {http://www.cstr.inf.ed.ac.uk/downloads/publications/2003/ijhci.pdf},
year = 2003
}
@inproceedings{AMIMLMI05,
author = {T. Hain and L. Burget and J. Dines and G. Garau and M.
Karafiat and M. Lincoln and I. McCowan and D. Moore and
V. Wan and R. Ordelman and S. Renals},
title = {The Development of the {AMI} System for the
Transcription of Speech in Meetings},
booktitle = {2nd Joint Workshop on Multimodal Interaction and
Related Machine Learning Algorithms},
abstract = {The automatic processing of speech collected in
conference style meetings has attracted considerable
interest with several large scale projects devoted to
this area. This paper describes the development of a
baseline automatic speech transcription system for
meetings in the context of the AMI (Augmented
Multiparty Interaction) project. We present several
techniques important to processing of this data and
show the performance in terms of word error rates
(WERs). An important aspect of transcription of this
data is the necessary flexibility in terms of audio
pre-processing. Real world systems have to deal with
flexible input, for example by using microphone arrays
or randomly placed microphones in a room. Automatic
segmentation and microphone array processing techniques
are described and the effect on WERs is discussed. The
system and its components presented in this paper yield
compettive performance and form a baseline for future
research in this domain.},
pdf = {http://www.cstr.inf.ed.ac.uk/downloads/publications/2005/AMIsystemMLMI05.pdf},
year = 2005
}
@inproceedings{AMIsystemICASSP2007,
author = {T. Hain and L. Burget and J. Dines and G. Garau and M.
Karafiat and M. Lincoln and J. Vepa and V. Wan},
title = {{The {AMI} System for the Transcription of Speech in
Meetings}},
booktitle = {Proc. {ICASSP}},
abstract = {This paper describes the AMI transcription system for
speech in meetings developed in collaboration by five
research groups. The system includes generic techniques
such as discriminative and speaker adaptive training,
vocal tract length normalisation, heteroscedastic
linear discriminant analysis, maximum likelihood linear
regression, and phone posterior based features, as well
as techniques specifically designed for meeting data.
These include segmentation and cross-talk suppression,
beam-forming, domain adaptation, web-data collection,
and channel adaptive training. The system was improved
by more than 20\% relative in word error rate compared
to our previous system and was usd in the NIST RTÂ’06
evaluations where it was found to yield competitive
performance.},
categories = {LVCSR, NIST Meeting Transcription Evaluation RT06S},
pdf = {http://www.cstr.inf.ed.ac.uk/downloads/publications/2007/ICASSP07.AMIasrsystem.pdf},
year = 2007
}
@inproceedings{Lin03,
author = {Lincoln, M. and Cox, S.J.},
title = {A Comparison of Language Processing Techniques for a
Constrained Speech Translation System},
booktitle = {IEEE Conference on Acoustics, Speech and Signal
Processing},
address = {Hong Kong},
abstract = {A system designed to allow Post Office counter clerks
to communicate with deaf customers by translating
speech into sign language is described. The system uses
approximately 370 pre-stored phrases which may be
signed to the customer using a specially designed
avatar. The clerk is unable to memorise this number of
phrases and therefore the system attempts to map from
their input speech to the semantically equivalent
pre-stored phrase. We describe a number of language
processing techniques developed to perform the mapping,
and give results obtained using alternative
formulations of the phrases from a number of speakers.
We then give results for recognised speech input and
show how mis-recognitions effect the mapping system.
Best performance is obtained using a mapping system
based on an entropy weighted, vector based distance
measure between the test phrase and each of the signed
phrases.},
categories = {visicast,sign language,translation,UEA},
pdf = {http://www.cstr.inf.ed.ac.uk/downloads/publications/2003/icassp2003.pdf},
year = 2003
}
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