POST: parallel object-oriented speech toolkit

Hennebert, Jean; Delacretaz, Dijana Petrovska

doi:10.1109/icslp.1996.608021

Cited by 5 publications

(2 citation statements)

References 3 publications

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“…These softwares, are WaveEdit [7], VISPER [8], Multi-Speech, Model 3700 [9], WINDSK [10], new collaborative active learning tool for signal processing [11], an Internet-based signal processing laboratory [12], SAPPHIRE [13], SPANNET [14], and software tool for introducing speech coding fundamental in a DSP Course [15,16]. Another set of software tools to enhance the local and distance learning for speech and signal processing classes [17] are POST [18] and ARES [19]. Reviews on the above existing softwares are essential for building a good education software.…”

Section: Existing Software Related To Speech Recognition Educationmentioning

confidence: 99%

Design of Educational Software for Automatic Speech Recognition (ASR) Techniques

Hong¹,

Salleh²

2012

Jurnal Teknologi

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Speech recognition has been an important subject for research, and it has come to a stage where it has been actively applied in a lot of industrial and consumer applications, overseas. However, speech recognition research is still in its infancy stage in Malaysia. The main reason is that speech recognition systems are highly complex and teaching students in this subject matter with the underlying technologies is a challenging task. Currently, some instructors use slide show presentations and white board in giving such courses. At the end of the course, students are not able to figure out the real output of the algorithms given. In this case, students are not exposed to the real technical systems and would easily get bored. This research is mainly on the improvement over the limitations and problems of the traditional teaching method in speech recognition by developing a set of interactive and practical education software to guide and assist students in studying, and performing experiments for speech recognition.

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Section: Existing Software Related To Speech Recognition Educationmentioning

confidence: 99%

Design of Educational Software for Automatic Speech Recognition (ASR) Techniques

Hong¹,

Salleh²

2012

Jurnal Teknologi

View full text Add to dashboard Cite

show abstract

“…This concept enables us to model behaviors of actors reacting directly to user-spoken commands. For speech recognition, we use POST, the Parallel Object oriented Speech Toolkit [21], developed for designing automatic speech recognition. It can perform simple feature extraction, training and testing of word and sub-word Hidden Markov Models with discrete and multi Gaussian statistical modeling.…”

Section: Speech Synthesis and Recognitionmentioning

confidence: 99%