Voice-Driven Modeling: Software Modeling Using Automated Speech Recognition

2019 ◽  
Author(s):  
Dana Black ◽  
Eric J. Rapos ◽  
Matthew Stephan
Keyword(s):  
Speech Recognition ◽  
Software Modeling ◽  
Automated Speech Recognition ◽  
Modeling Software

scholarly journals Realization of speech in design intent of geometric modelling

2017 ◽  
Vol 7 (1.3) ◽  
pp. 121
Author(s):  
Sreeja B P ◽  
Amrutha K G ◽  
Jeni Benedicta J ◽  
Kalaiselvi V ◽  
Ranjani R
Keyword(s):  
Speech Recognition ◽  
Geometric Modeling ◽  
Geometric Modelling ◽  
Design Intent ◽  
Voice Input ◽  
Interactive Mode ◽  
Modeling Software ◽  
Speech Recognition Engine ◽  
The Voice ◽  
Geometric Designs

The conventional interactive mode is especially used for geometric modeling software. This paper describes, a voice-assisted geometric modeling mechanism to improve the performance of modeling, speech recognition technology is used to design this model. This model states that after receiving the voice command, the system uses the speech recognition engine to identify the voice commands, then the voice commands identified are parsed and processed to generate the geometric design based on the users voice input dimensions, The outcome of the system is capable of generating the geometric designs to the user via speech recognition. This work also focuses on receiving the feedback from the users and customized the model based on the feedback.

scholarly journals Comparison of Two Forced Alignments Systems for Aligning Bribri Speech

2017 ◽  
Author(s):  
Sofía Flores Solórzano ◽  
Rolando Coto-Solano
Keyword(s):  
Natural Language Processing ◽  
Speech Recognition ◽  
Language Processing ◽  
Indigenous Languages ◽  
Future Research ◽  
Automated Speech Recognition ◽  
Recognition Systems ◽  
Para Determinar ◽  
Future Work ◽  
Manual Correction

Abstract: Forced alignment provides drastic savings in time when aligning speech recordings and is particularly useful for the study of Indigenous languages, which are severely under-resourced in corpora and models. Here we compare two forced alignment systems, FAVE-align and EasyAlign, to determine which one provides more precision when processing running speech in the Chibchan language Bribri. We aligned a segment of a story narrated in Bribri and compared the errors in finding the center of the words and the edges of phonemes when compared with the manual correction. FAVE-align showed better performance: It has an error of 7% compared to 24% with EasyAlign when finding the center of words, and errors of 22~24 ms when finding the edges of phonemes, compared to errors of 86~130 ms with EasyAlign. In addition to this, EasyAlign failed to detect 7% of phonemes, while also inserting 58 spurious phones into the transcription. Future research includes verifying these results for other genres and other Chibchan languages. Finally, these results provide additional evidence for the applicability of natural language processing methods to Chibchan languages and point to future work such as the construction of corpora and the training of automated speech recognition systems.  Spanish Abstract: El alineamiento forzado provee un ahorro drástico de tiempo al alinear grabaciones del habla, y es útil para el estudio de las lenguas indígenas, las cuales cuentan con pocos recursos para generar corpus y modelos computacionales. Aquí comparamos dos sistemas de alineamiento, FAVE-align e EasyAlign, para determinar cuál provee mayor precisión al alinear habla en la lengua chibcha bribri. Alineamos una narración y comparamos el error al tratar de encontrar el centro de las palabras y los bordes de los fonemas con sus equivalentes en una corrección manual. FAVE-align tuvo mejor rendimiento, con un error de 7% comparado con 24% de EasyAlign para el centro de las palabras, y con errores de 22~24 ms para el borde de los fonemas, comparado con 86~130 ms con EasyAlign. Además, EasyAlign no pudo detectar el 7% de los fonemas, y al mismo tiempo añadió 58 sonidos espurios a la transcripción. Como trabajo futuro verificaremos estos resultados con otros géneros hablados y con otras lenguas chibchas. Finalmente, estos resultados comprueban la aplicabilidad de los métodos de procesamiento de lengua natural a las lenguas chibchas, y apuntan a trabajo futuro en la construcción de corpus y el entrenamiento de sistemas de reconocimiento automático del habla.

The Role of Automated Speech Recognition in Endoscopic Data Collection

Endoscopy ◽  
1992 ◽  
Vol 24 (S 2) ◽  
pp. 493-498 ◽  
Author(s):  
R. S. Johannes ◽  
D. L. Carr-Locke
Keyword(s):  
Speech Recognition ◽  
Data Collection ◽  
Automated Speech Recognition

scholarly journals Automated Speech Recognition Systems and Older Adults: A Literature Review and Synthesis

2019 ◽  
Vol 63 (1) ◽  
pp. 42-46 ◽  
Author(s):  
Lauren Werner ◽  
Gaojian Huang ◽  
Brandon J. Pitts
Keyword(s):  
Older Adults ◽  
Speech Recognition ◽  
Current Knowledge ◽  
Age Groups ◽  
Older Individuals ◽  
Age Related ◽  
Wide Range ◽  
Automated Speech Recognition ◽  
Technological Developments ◽  
Physical Changes

The number of older adults is growing significantly worldwide. At the same time, technological developments are rapidly evolving, and older populations are expected to interact more frequently with such sophisticated systems. Automated speech recognition (ASR) systems is an example of one technology that is increasingly present in daily life. However, age-related physical changes may alter speech production and limit the effectiveness of ASR systems for older individuals. The goal of this paper was to summarize the current knowledge on ASR systems and older adults. The PRISMA method was employed and 17 studies were compared on the basis of word error rate (WER). Overall, WER was found to be influenced by age, gender, and the number of speech samples used to train ASR systems. This work has implications for the development of future human-machine technologies that will be used by a wide range of age groups.

Automated speech recognition for time recording in out-of-hospital emergency medicine—an experimental approach

Resuscitation ◽  
2004 ◽  
Vol 60 (2) ◽  
pp. 205-212 ◽  
Author(s):  
J Gröschel ◽  
F Philipp ◽  
St Skonetzki ◽  
H Genzwürker ◽  
Th Wetter ◽  
...  
Keyword(s):  
Emergency Medicine ◽  
Speech Recognition ◽  
Experimental Approach ◽  
Hospital Emergency ◽  
Automated Speech Recognition
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