# Speech Processing

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## 1. General information and organization issues
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- Voice-based human-machine communication via HMI - Human Machine Interface
- Dialogue systems like chatbox
- the middle part is called Natural Language Processing (NLP)
- TTS: Text-to-Speech
- ASR: Automatic Speech Recognition
- speech transcription from acoustic to text form
- replacement of keyboard by voice
- automated transcription of audio records/streams
- speaker recognition
- system of biometrics identification for autorization purposes, forensic applications
- human articulatory system
- speech production model
- samples of different parts of speech signal
- plosive sound is hard to deal with because of short duration
- general description of speech signal
- acoustic level: purely analyze waveform and signal itself without considering content
- phonetic level: information content, try to separate it into subwords
- signal sampling and quantization, Pulse Code Modulation(PCM)
- speech sampling
- linear quantization of speech signal
- freq. perception
- itensity
- loudness
> freq. 200 to 5000, we have the highest sensitivity for the sounds
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## 2. Basic time-domain and spectral characteristics of speech signal
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- Most of them are mathematical eq., check slide.
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