Audio Processing and Automation with Python

Understand how to convert analog waveforms into numbers via sampling, clean and filter audio, and extract features like pitch and spectrogram to train AI models and predict live data.

Explore how voice assistants analyze audio data by capturing voice with a microphone, preprocessing to remove noise, extracting features like MFCCs and spectrograms, and predicting actions with AI models.

Explore python functions by creating and calling them with def, parameters, and arguments; learn how functions save code, improve readability, and enable reuse through examples and nested calls.

Explore pure functions in advanced Python, showing no side effects and identical outputs for identical inputs, with examples like square and add, and contrast to higher order functions.

Explore lambda functions in Python, including syntax and anonymous inline single-expression functions, with examples of single and multiple arguments, passing as parameters, and operations like add, multiply, and average.

Explore Python for loops and iterating over lists, tuples, dictionaries, and strings. Use range with start, stop, and step to generate sequences and print results.

Learn how the Python while loop works, including its condition and increment or decrement with addition assignment, and compare with the for loop through practical examples.

Explore NumPy, a Python-based library for scientific computing, enabling multi-dimensional arrays and matrices, array operations like mean, max, and min, plus slicing, indexing, and basic environment setup.

Learn pandas, a Python library for data manipulation and analysis, including series and data frames. Work with csv, json, and excel formats and perform filtering, sorting, merging, and grouping.

Learn how to visualize data with matplotlib in Python, creating line, bar, scatter, density, and area plots using matplotlib.pyplot, pandas data frames, and basic installation tips.

Explore how the Django web framework enables rapid development of Python web applications, covering installation, project and app structure, views, templates, URLs, and running a local server.

Explore python-based audio automation by loading, cutting, and exporting audio segments with a py dub workflow, using a cut_audio_segment function and step-by-step Visual Studio Code source code.

Learn to convert audio formats with python using the pydub library and pachyderm-based steps, including mp3 to wav conversion, loading, and exporting.

Learn to control audio playback speed with Python by loading audio with audio segment, using the speed up library, and exporting a faster mp3 in VS Code.

Learn to merge two audio files in python using an overlay with the py dub audio segment library, loading both files, merging them, and exporting the result as mp3.

Learn to add two audio files using python and pydub, distinguishing addition from merging, and export the concatenated result with configurable input and output paths.

Apply an echo effect to an audio file using Python. Load the audio, set a delay in milliseconds, create a delayed copy, overlay and export.

Learn to add a reverb effect to audio in Python using the pydub library, by defining add_reverb with delay and decay and exporting the processed file.

Learn to remove noise from audio using python, performing simple spectral subtraction, loading audio, converting to numpy arrays, and exporting a cleaned wav file for improved sound in video production.

Learn to automate audio volume with python using the pi dove library, loading audio via the audio segment class and exporting files with increased or decreased volume by db values.

Learn to apply fat in and fat out effects to audio with Python by loading audio, setting durations in milliseconds, and exporting the processed fade in/out audio.

Learn to reverse audio with Python automation by loading audio via the AudioSegment class from the Pi Dub library, then reverse and export it.

Learn to convert text to speech using python and a text-to-speech library, initialize the engine, supply text, and generate a male or female voice in 3–4 lines of code.

Convert text to speech with Python using the same code, then switch from a male to a female narrator by adjusting Windows control panel settings.

Discover converting text to speech in Python using the dt ts library, create a g t s object with language, and save the resulting audio as voice.mp3.

Learn to convert audio to text using Python and speech recognition, loading audio files, recording data, and using recognize_google to produce text for pdfs or text files.

Design a Python script for audio automation that uses OCR with pytesseract and PIL to extract text from an image and feed it to a text-to-speech engine.

Learn to download a YouTube video as audio with Python using the pie tube library, filtering for audio streams and saving as mp3 in a compact six-line script.

Learn to read a web page using python by fetching the page with requests, parsing HTML with BeautifulSoup, extracting paragraphs, and converting the text to speech with pyttsx3.

Convert video to audio using python and moviepy, detailing steps to load a video, extract its audio, and save the converted audio file offline in VS Code.

This lecture demonstrates extracting audio features from a file in Python, including MFCCs, chroma features, spectral centroid, spectral contrast, zero crossing rate, and spectral bandwidth.