This report represents a collection of papers published in various conference proceedings that are not readily available for researchers working in the field of speech recognition. The papers reprinted are: 1. Reddy — Speech Input Terminals (June 1970). 2. Reddy, Erman, and Neely — The CMU Speech Recognition Project (October 1970). 3. Erman and Reddy — Telephone Speech (August 1971). 4. Neely a...

Speech synthesis has changed dramatically in the past few years to have a corpus-based focus, borrowing heavily from advances in automatic speech recognition. In this paper, we survey technology in speech recognition systems and how it translates (or doesn’t translate) to speech synthesis systems. We further speculate on future areas where ASR may impact synthesis and vice versa.

In this paper we consider a feature estimation approach for vocal fold pathology classification, based on digital signal processing theory. This problem is addressed by formulating a stochastic maximum likelihood (ML) estimation procedure, based on Estimation-Maximization (EM) algorithm. New spectral parameters of speech, noted as Spectral Pathology Component (SPC) is estimated. For classificat...

Traditional speech processing methods for laryngeal pathology assessment assume linear speech production, with measures derived from an estimated glottal ow waveform. They normally require the speaker to achieve complete glottal closure, which for many vocal fold pathologies cannot be accomplished. To address this, a nonlinear signal processing approach is proposed which employs a di erential T...

One area of voice research that has historically been understudied is the interaction between voice pathology and acoustic aspects of the speech signal that affect intelligibility. Landmark-based software tools are particularly suited to fast, automatic analysis of small, non-lexical differences in the acoustic signal reflecting the production of speech. We are building a tool set that provides...

(1) Post Graduation Program in Dentistry at Piracicaba School of Dentistry, Campinas State University – FOP-UNICAMP, Piracicaba-SP, Brazil. (2) University of Sagrado Coração, Bauru-SP, Brazil. (3) Speech-language pathologist; PhD Professor of the Speech-Language Pathology Department at Bauru School of Dentistry, University of São Paulo FOB-USP, Bauru-SP, Brazil; PhD in Physiopathology in Medica...

In this paper, the feasibility of a system developed for the remote diagnosis of voice pathologies is analysed. More specifically, the performance of MFCC-based pathology detectors over speech transmitted through an analogue telephone channel is studied. Results indicate that MFCC are voice features fairly robust to amplitude distortion and almost insensitive to phase distortion, but the effici...

The recognition and training algorithms for autoregressive hidden Markov models were developed in order to solve the task of vocal fold pathology detection. Three databases were created and used for 3 vocal pathologies detection. During the experiments the proposed vocal tract pathology detection system based on autoregressive hidden Markov models and wide-range AFT mel-spectrum provides very h...