https://github.com/nuniz/speech-audio-ml-interview

Speech & Audio Algorithms and Machine Learning Interview Questions
https://github.com/nuniz/speech-audio-ml-interview

algorithms audio data-science interview interview-preparation interview-questions job machie-learning questions sound speech

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Speech & Audio Algorithms and Machine Learning Interview Questions

• Host: GitHub
• URL: https://github.com/nuniz/speech-audio-ml-interview
• Owner: nuniz
• License: mit
• Created: 2024-03-13T20:09:53.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2024-12-31T08:31:45.000Z (over 1 year ago)
• Last Synced: 2025-03-23T16:43:32.455Z (about 1 year ago)
• Topics: algorithms, audio, data-science, interview, interview-preparation, interview-questions, job, machie-learning, questions, sound, speech
• Homepage:
• Size: 310 KB
• Stars: 7
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Speech & Audio Interview Questions

Feel free to dive into any section that interests you :-)

![Diagram](images/diagram-v1.png)

Table of contents

- [Speech \& Audio Algorithms and Machine Learning](#speech--audio-algorithms-and-machine-learning)

- [Table of contents](#table-of-contents)

- [Acoustics ](#acoustics-)

  - [Sound ](#sound-)

  - [Reverberation ](#reverberation-)

- [Electronics ](#electronics-)

- [Signal Processing ](#signal-processing-)

  - [Digital Filtering ](#digital-filtering-)

  - [Audio Features ](#audio-features-)

  - [Audio Transforms ](#audio-transforms-)

  - [Compression ](#compression-)

  - [Noise Reduction ](#noise-reduction-)

- [Deep Learning ](#deep-learning-)

  - [Sound Classification ](#sound-classification-)

  - [Speech Enhancement ](#speech-enhancement-)

  - [Speaker Recognition ](#speaker-recognition-)

  - [Speech Recognition ](#speech-recognition-)

# Acoustics 

## Sound 

* What is the difference between sound power and sound intensity?

* How do we convert sound pressure between dB SPL and pascals (Pa)?

* What’s the difference between dB SPL and dB(A)?

* How do density and elasticity of a medium affect sound speed?

* What is the Doppler effect, and how does it work?

## Reverberation 

* What is room impulse response (RIR), and how is it measured?

* What are the effects of reverberation in room acoustics?

* How is reverberation measured (RT60)?

* How can we simulate reverberation digitally?

* What methods are used to analyze time delay in audio signals?

# Electronics 

* What should you consider when choosing a microphone?

* How do you calibrate a microphone?

* What is an Anti-Aliasing filter?

* What are typical sampling rates and bit ranges for audio?

* What are the common interfaces used in digital audio systems?

# Signal Processing 

## Digital Filtering 

* How do FIR and IIR filters differ?

* What does the filtfilt function do?

* How does a preamplifier work in a microphone setup?

* How is zero-phase filtering done, and what are its benefits?

* How can we test the stability of digital filters?

## Audio Features 

* What is signal energy, and how do we calculate it?

* What are the uses of ZCR and FFT in audio analysis?

* How can we estimate the pitch of speech?

* What are common audio features, and how do we extract them?

* How can we test the similarity between two audio signals?

## Audio Transforms 

* What is STFT, and how is it done?

* What are the key considerations when implementing STFT?

* What is MFCC used for in audio processing?

## Compression 

* How does the number of quantizer levels change the dynamic range?

* How does AD-PCM work?

* What is LPC, and how does it represent speech?

* How is mu-law quantization different from linear quantization?

## Noise Reduction 

* How does spectral subtraction work?

* What is the Wiener filtering method?

* When is wavelet-based denoising useful?

* What is Speech Presence Probability (SPP), and how is it used?

* How is adaptive filtering used for noise reduction and echo cancellation?

# Deep Learning 

## Sound Classification 

* What are the challenges in sound classification?

* How is deep learning used in sound classification?

* What metrics evaluate classification models?

## Speech Enhancement 

* What deep networks are common for speech enhancement?

* How is phase handled in speech enhancement?

* Why might MSE not be the best loss function?

* What metrics evaluate speech enhancement models?

## Speaker Recognition 

* What’s the difference between diarization, identification, and verification?

* What networks are used for speaker recognition?

* What are speaker embeddings, and how are they used?

* How are x-vectors different from i-vectors?

## Speech Recognition 

* What methods are used for speech recognition?

* How is audio prepared for speech recognition?

* How are speech recognition models evaluated?

* How does Whisper use weak supervision?

* What is the Whisper model architecture?

* What are the key features and differences between Wav2Vec models?

* How does CTC encoding help Wav2Vec?

* What’s the role of Beam Search in Wav2Vec?