Segment vocoder based on reconstruction with natural segments

Jeanrenaud, P.; Peterson, P.

doi:10.1109/icassp.1991.150412

Cited by 10 publications

(4 citation statements)

References 3 publications

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“…As a result of not using segment to segment warping, [CL94] show that their method outperforms that of [SH88]. Moreover, [CL94] note that a related work Jeanrenaud and Peterson [JP91,PJV90] from BBN, is more close to their formulation, in the sense that [JP91] use duration dependent segment codebooks, which is populated (and designed by means of an iterative algorithm) with segments of variable lengths, but ensuring that it has sub-codebooks each with several segments of a fixed length. However, it should be noted that having a variable length segment codebook and allowing for warping based segment quantization allows a particular segment representing a particular acoustic realization of speech to quantize a varied number of input segments belonging to the same acoustic category; in the absence of such a warping of a particular segment in the codebook, the codebook is constrained to have segments of different lengths to match with the different realizations of the same acoustic category (i.e.…”

Section: Variable-to-variable Length Vector Quantizationmentioning

confidence: 93%

Ultra Low Bit-Rate Speech Coding

Ramasubramanian¹,

Doddala²

2015

SpringerBriefs in Electrical and Computer Engineering

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The authors of this series have been hand-selected. They comprise some of the most outstanding scientists -drawn from academia and private industry -whose research is marked by its novelty, applicability, and practicality in providing broad based speech solutions. The SpringerBriefs in Speech Technology series provides the latest findings in speech technology gleaned from comprehensive literature reviews and empirical investigations that are performed in both laboratory and real life settings. Some of the topics covered in this series include the presentation of real life commercial deployment of spoken dialog systems, contemporary methods of speech parameterization, developments in information security for automated speech, forensic speaker recognition, use of sophisticated speech analytics in call centers, and an exploration of new methods of soft computing for improving human-computer interaction. Those in academia, the private sector, the self-service industry, law enforcement, and government intelligence, are among the principal audience for this series, which is designed to serve as an important and essential reference guide for speech developers, system designers, speech engineers, linguists, and others. In particular, a major audience of readers will consist of researchers and technical experts in the automated call center industry where speech processing is a key component to the functioning of customer care contact centers.Amy Neustein, Ph.D., serves as Editor-in-Chief of the International Journal of Speech Technology (Springer). She edited the recently published book "Advances in Speech Recognition: Mobile Environments, Call Centers and Clinics" (Springer 2010), and serves as quest columnist on speech processing for Womensenews. Dr. Neustein is Founder and CEO of Linguistic Technology Systems, a NJ-based think tank for intelligent design of advanced natural language based emotion-detection software to improve human response in monitoring recorded conversations of terror suspects and helpline calls. Dr. Neustein's work appears in the peer review literature and in industry and mass media publications. Her academic books, which cover a range of political, social and legal topics, have been cited in the Chronicles of Higher Education, and have won her a Pro Humanitate Literary Award. She serves on the visiting faculty of the National Judicial College and as a plenary speaker at conferences in artificial intelligence and computing. Dr. Neustein is a member of MIR (machine intelligence research) Labs, which does advanced work in computer technology to assist underdeveloped countries in improving their ability to cope with famine, disease/illness, and political and social affliction. She is a founding member of the New York City Speech Processing Consortium, a newly formed group of NY-based companies, publishing houses, and researchers dedicated to advancing speech technology research and development.

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Section: Variable-to-variable Length Vector Quantizationmentioning

confidence: 93%

Ultra Low Bit-Rate Speech Coding

Ramasubramanian¹,

Doddala²

2015

SpringerBriefs in Electrical and Computer Engineering

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“…For speaker independent coding, some type of speaker adaptation may be performed. One possible method is to choose the best codebook from a set of multiple-speaker codebooks [3]. Another is to adapt the codebook to a new speaker [8,9].…”

Section: Introductionmentioning

confidence: 99%

Improving speaker recognisability in phonetic vocoders

Ribeiro¹,

Trancoso²

1998

5th International Conference on Spoken Language Processing (ICSLP 1998)

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Phonetic vocoding is one of the methods for coding speech below 1000 bit/s. The transmitter stage includes a phone recogniser whose index is transmitted together with prosodic information such as duration, energy and pitch variation. This type of coder does not transmit spectral speaker characteristics and speaker recognisability thus becomes a major problem. In our previous work, we adapted a speaker modification strategy to minimise this problem, modifying a codebook to match the spectral characteristics of the input speaker. This is done at the cost of transmitting the LSP averages computed for vowel and glide phones. This paper presents new codebook generation strategies, with gender dependence and interpolation frames, that lead to better speaker recognisability and speech quality. Relatively to our previous work, some effort was also devoted to deriving more efficient quantization methods for the speakerspecific information, that considerably reduced the average bit rate, without quality degradation. For the CD-ROM version, a set of audio files is also included.

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“…For speaker independent coding, some type of speaker adaptation may be performed. One possible method is to choose the best codebook from a set of multiple codebooks [3]. Another, is to adapt the codebook to a new speaker [6].…”

Section: Introductionmentioning

confidence: 99%

Phonetic vocoding with speaker adaptation

Ribeiro¹,

Trancoso²

1997

5th European Conference on Speech Communication and Technology (Eurospeech 1997)

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This paper describes a phonetic vocoding scheme which relies on speaker adaptation to capture important speaker characteristics. These are typically lost in phonetic vocoders which transmit only information about the phones which are recognized, together with some prosodic information. In our scheme, however, additional speaker characteristics are transmitted in vowel regions (average values of LSP coefficients for each phone). This additional information yielded potentially good speaker recognizability results, in informal listening tests, while still achieving a rather low average bit rate, suitable for many transmission and storage applications. This work extends our previous phonetic vocoding scheme described in [5]. The vocoder is now fully quantized and the number of transmitted parameters had been significantly reduced.

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Segment vocoder based on reconstruction with natural segments

Cited by 10 publications

References 3 publications

Ultra Low Bit-Rate Speech Coding

Ultra Low Bit-Rate Speech Coding

Improving speaker recognisability in phonetic vocoders

Phonetic vocoding with speaker adaptation

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