Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

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

Last synced: about 1 month ago
JSON representation

Speech & Audio Algorithms and Machine Learning Interview Questions

Awesome Lists containing this project

README 

        
# Speech & Audio Algorithms and Machine Learning



Feel free to dive into any section that interests you or aligns with your focus.



# 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 sound intensity, and how do acoustic instruments measure it?

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

* Discuss the difference between dB SPL and dB(A) scales. 

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



## Reverberation 



* What is room impulse response (RIR), and how do we measure it?

* Discuss the concept of reverberation and its implications in room acoustics.

* What methods are used to measure reverberation? (RT60)

* How does the GCC-PHAT algorithm differ from cross-correlation?



# Electronics 



* What factors would you consider when selecting a microphone?

* Describe the microphone calibration process.

* Describe the process of converting analog signals into digital data.

* What is the role of an Anti-Aliasing filter?

* What are the typical sampling rates and range of bits commonly used in audio?

* What digital protocols are used in microphones, such as I2S (Inter-IC Sound) and PCM (Pulse Code Modulation)?



# Signal Processing 



## Digital Filtering 



* What are the key differences between Finite Impulse Response (FIR) and Infinite Impulse Response (IIR) filters?

* Explain the usage of the filtfilt function.

* How can zero-phase filtering be implemented, and what advantages does it offer?

* What are the various methods for testing the stability of digital filters?



## Audio Features 



* What is energy in the context of speech signals, and how is it computed?

* What are the advantages of using the zero-crossing rate (ZCR) compared to the Fast Fourier Transform (FFT)?

* What methods are commonly used to estimate the pitch of a speech signal?

* What are some common audio features, and how are they extracted?

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



## Audio Transforms 



* Explain the Short-Time Fourier Transform (STFT) and its implementation.

* Why do we use zero padding in STFT?

* Why do we use overlap and windowing in STFT?

* What are the trade-offs when determining the STFT parameters?

* What do people usually use Mel-frequency cepstral coefficients (MFCC) for in audio processing?



## Compression 



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

* Describe the operation of an adaptive differential pulse code modulation (AD-PCM).

* What is linear predictive coding (LPC), and how does it represent speech signals?

* How does the mu-law quantization differ from linear quantization, and what advantages does it offer?



## Noise Reduction 



* How does spectral subtraction work?

* What is the Wiener filtering method?

* When are wavelet-based denoising techniques effective?

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

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



# Deep Learning 



## Sound Classification 



* What challenges are faced in sound classification tasks?

* How can deep learning be applied to sound classification?

* What metrics assess classification model performance?



## Speech Enhancement 



* What deep network architectures are common for speech enhancement?

* How is the phase treated in speech enhancement?

* What loss functions are typical in speech enhancement, and why might Mean Squared Error (MSE) have limitations?

* Which objective metrics evaluate speech enhancement, and how do they differ?



## Speaker Recognition 



* Distinguish between speaker diarization, identification, and verification.

* What are typical deep network architectures for speaker recognition?

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

* What are x-vectors, and how do they differ from i-vectors?



## Speech Recognition 



* What methods are used in speech recognition?

* How is audio data preprocessed for speech recognition?

* What evaluation methods are used for speech recognition models?

* How does Whisper employ weak supervision, and what is its architecture?

* Describe training and optimization for Whisper models.

* What distinguishes Wav2Vec2 from Wav2Vec?

* How does CTC encoding address limitations in decoding Wav2Vec outputs?

* Explain the role of Beam Search in Wav2Vec models.