Reconstructing intelligible audio speech from visual speech features

This work describes an investigation into the feasibility of producing intelligible audio speech from only visual speech fea- tures. The proposed method aims to estimate a spectral enve- lope from visual features which is then combined with an arti- ficial excitation signal and used within a model of speech pro- duction to reconstruct an audio signal. Different combinations of audio and visual features are considered, along with both a statistical method of estimation and a deep neural network. The intelligibility of the reconstructed audio speech is measured by human listeners, and then compared to the intelligibility of the video signal only and when combined with the reconstructed audio

Applying prosodic speech features in mental health care: An exploratory study in a life-review intervention for depression

The present study aims to investigate the application of prosodic speech features in a psychological intervention based on lifereview. Several studies have shown that speech features can be used as indicators of depression severity, but these studies are mainly based on controlled speech recording tasks instead of natural conversations. The present exploratory study investigated speech features as indicators of depression in conversations of a therapeutic intervention. The changes in the prosodic speech features pitch, duration of pauses, and total duration of the participant's speaking time were studied over four sessions of a life-review intervention for three older participants. The ecological validity of the dynamics observed for prosodic speech features could not be established in the present study. The changes in speech features differed from what can be expected in an intervention that is effective in decreasing depression and were inconsistent with each other for each of the participants. We suggest future research to investigate changes within the intervention sessions, to relate the changes in feature values to the topical content of the speech, and to relate the speech features directly to depression scores

Automatic speech intelligibility detection for speakers with speech impairments: the identification of significant speech features

Selection of relevant features is important for discriminating speech in detection based ASR system, thus contributing to the improved performance of the detector. In the context of speech impairments, speech errors can be discriminated from regular speech by adopting the appropriate discriminative speech features with high discriminative ability between the impaired and the control group. However, identification of suitable discriminative speech features for error detection in impaired speech was not well investigated in the literature. Characteristics of impaired speech are grossly different from regular speech, thus making the existing speech features to be less effective in recognizing the impaired speech. To overcome this gap, the speech features of impaired speech based on the prosody, pronunciation and voice quality are analyzed for identifying the significant speech features which are related to the intelligibility deficits. In this research, we investigate the relations of speech impairments due to cerebral palsy, and hearing impairment with the prosody, pronunciation, and voice quality. Later, we identify the relationship of the speech features with the speech intelligibility classification and the significant speech features in improving the discriminative ability of an automatic speech intelligibility detection system. The findings showed that prosody, pronunciation and voice quality features are statistically significant speech features for improving the detection ability of impaired speeches. Voice quality is identified as the best speech features with more discriminative power in detecting speech intelligibility of impaired speech

Therapy Progress Indicator (TPI): Combining speech parameters and the subjective unit of distress

A posttraumatic stress disorder (PTSD) is a severe handicap in daily life and its treatment is complex. To evaluate the success of treatments, an objective and unobtrusive expert system was envisioned: an therapy progress indicator (TPI). Speech was considered as an excellent candidate for providing an objective, unobtrusive emotion measure. Speech of 26 PTSD patients was recorded while they participated in two reliving sessions: re-experiencing their last panic attack and their last joyful occasion. As a subjective measure, the subjective unit of distress was determined, which enabled the validation of derived speech features. A set of parameters of the speech features: signal, power, zero crossing ratio, and pitch, was found to discriminate between the two sessions. A regression model involving these parameters was able to distinguish between positive and negative distress. This model lays the foundation for an TPI for patients with PTSD, which enables objective and unobtrusive evaluations of therapies

AN ANALYSIS OF FEATURES AND FUNCTIONS IN WOMEN’S SPEECH IN THE TALKSHOW UNITED STATES OF WOMEN SUMMIT

AbstractThis study aims at denoting the features of female speech and its functions that Michelle Obama applied in the Talk Show United States of Women Summit. In addition, the purpose of this study is to also denote the features of male speech, so as to see which feature is the most dominant in use. The study results in the finding of 18 data of women's utterances. There are 7 types of speech features consisting of 2 data adjectives, 1 datum of tag question, 2 data of raising intonations on declaratives, 1 datum of avoidance of strong swear words, 6 data of emphatic stress, 2 data of lexical hedges and 3 data of intensifiers. The female speech features in the analysis serve as hedges device and booster device. The present writer also sees that Michelle uses two types of male speech features in 4 data, they are 3 pieces of minimal responses and 1 command and directive. Therefore, it can be said that the use of female speech features in this research are more dominant than male's.Keywords: men’s speech features, women’s speech features, functions of women’s speech features