Speech Recognition: Learn Digital Signal Processing

  • Thread starter CylonMath
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In summary, the conversation discusses the creation of a Speech Recognition Software for personal use and the necessary subjects to learn for processing sound data. The speaker mentions their knowledge in Fourier series and transforms but asks for guidance on what else they should know. They are also provided with resources for further information on speech recognition technology, including Dragon Natural Speaking and Mac Speech.
  • #1
CylonMath
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Hello , I want to do a small Speech Recognition Software for my pc , to allow me use my voice to start some programs and execute some commands on shell ( I know there are others but i want to do in on the educational side)

What subjects i should learn first ? I haven't taken Digital Signal Processing courses yet, however i have knowledge in Fourier series and transforms. What should i know to process sound data ?

Can you describe briefly , thanks !
 
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  • #3
Thank you , that explains briefly.
 
  • #4
As an FYI Dragon Natural Speaking is favored by the Doc and Attorneys I support. It is a big resource hog so a beefy PC is recommended.

http://www.nuance.com/naturallyspeaking/

I use Mac Speech on the OS X as well. It is impressive. It is built upon Dragon's engine.
http://www.macspeech.com/

I know you wanted to write something, but these might save you some time.
 

Related to Speech Recognition: Learn Digital Signal Processing

1. What is speech recognition?

Speech recognition is the process of converting spoken words into digital text that a computer can understand and process. It involves using algorithms and computer programs to analyze the sound waves of speech and match them to known patterns and words.

2. How does speech recognition work?

Speech recognition works by breaking down speech into smaller units, such as phonemes and words, and using statistical models and pattern recognition to match them to known patterns and words. It also involves using language and grammar models to improve accuracy and context understanding.

3. What is digital signal processing?

Digital signal processing is the manipulation and analysis of digital signals, such as sound waves, using mathematical algorithms and techniques. It is used in speech recognition to extract and analyze features of speech signals, such as amplitude, frequency, and duration, to identify and recognize speech patterns.

4. What are some applications of speech recognition?

Speech recognition has many practical applications, such as voice-controlled virtual assistants, dictation software, voice-activated smart devices, and automated phone systems. It is also used in security and surveillance, language translation, and speech-to-text transcription.

5. What are the challenges of speech recognition?

Some of the challenges of speech recognition include dealing with background noise, variations in accents and speech patterns, and understanding context and intent. Improving accuracy and speed of recognition are also ongoing challenges. Additionally, speech recognition technology must be continuously trained and updated to keep up with language changes and new vocabulary.

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