11/24/2023 0 Comments Praat voice analysis scriptsNCHLT Speech Corpus (at least one language).It’s also possible now to refine the search results using filters (age, gender, and location). You can view the results in a table (including orthographic transcription, speaker ID, age, gender, and location) and open corresponding audio files one after the other or specifically for certain items in the results list. XML parsing and search is done inside the Praat script (this is considerably slower but more robust than doing it with Python like before). The corpus can be obtained from the South African Centreįor Digital Language Resources (SADiLaR) website.Īfter launching this plugin, you select one of your installed languages and specify a search pattern (simple pattern or regular expression). The NCHLT Speech Corpus (National Centre for Human Language Technologies, Council for Scientific and Industrial Research, South Africa) contains orthographically transcribed broadband speech corpora for all of South Africa’s eleven official languages and must be available on your machine (at least one language) before using this plugin. It is argued that this kind of investigation is possible only within a focused training program, given by a faculty who has agreed on the goals.This plugin enables Praat to search in the orthographic transcriptions of the NCHLT Speech Corpus and open the audio files of corresponding search results. High-resolution computerized recording, complemented with an acoustic register marker, allows a meaningful assessment of some effects of training, on an individual basis and for groups that comprise singers of a specific genre. These changes were manifest also in the average group. VRPs of individual voices were seen to change over the course of a singing education. The students& amp amp amp amp amp #39 self-evaluations of the voice changes appeared in some cases to contradict the VRP findings. Pre/post comparison of the average VRPs showed, in the midrange, (1) a decrease in the VRP area that was associated with the loud chest voice, (2) a reduction of the crest factor values, and (3) a reduction of maximum sound pressure level values. Findings were compared with the self-assessed vocal changes. Also, a mapping within the VRP of voice quality, as expressed by the crest factor, was used to indicate the register boundaries and to monitor the acoustical consequences of the newly learned vocal technique of & amp amp amp amp amp quot mixed voice.& amp amp amp amp amp quot VRPs were averaged across subjects. The VRP perimeter contour was analyzed for effects of voice training. Based on the responses, a subgroup of 10 classically trained female voices was selected, which was homogeneous enough for effects of training to be identified. A questionnaire that included questions on optimal range, register use, classification, vocal health and hygiene, mixing technique, and training goals was used to rate and categorize self-assessed voice changes. Pretraining and posttraining recordings were made of students who participated in a 3-year bachelor singing study program. Phonetograms were suggested to be useful for visual feedback and documentation of changes in voice therapy for M-F TS clients.Ī longitudinal study was performed on the acoustical effects of singing voice training under a given study program, using the voice range profile (VRP). Instrumental and subjective data suggested that the use of low speech intensities and avoidance of vocal fry could help contribute to a successful female voice. Phonetogram speech-range data fell between male and female data.The importance of speaking fundamental frequency (SFF) in perception of gender was confirmed. The speech sound pressure level (SPL) was higher than the female norms. The aerodynamic data agreed with normative male high-pitch data. No data indicated hyperfunctional vocal behavior. Perceptual ratings of strain and breathiness were low. Background data did not account for female voice success. Fundamental frequency (F0) accounted for 41–49% of variation in gender ratings for the group, but individual exceptions were found. M-F TS data were compared with male and female normative data.Agreement between naive and voice-expert listeners as well as intra- and interlistener reliability was good. Relationships among acoustical and aerodynamic measurements, background data, self-evaluations, and auditory perceptual ratings were examined. All recordings were made in typical- and loud-voice conditions. Transglottal air pressure and airflow were estimated from oral recordings. The aim was to examine the usefulness of phonetograms and aerodynamic measures for voice assessment of this client group.Descriptive and correlational.Phonetogram speech-range profiles (SRPs) were recorded for the M-F TS participants' attempted female voice. This exploratory study reports instrumental and subjective data for 25 male-to-female transsexual (M-F TS) individuals using their attempted female voice.
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