Focusing on Python libraries specific to audio processing opens a vast array of possibilities for handling audio data, from simple playback and recording to complex audio analysis and signal processing tasks. Beyond `Librosa`, which is tailored more towards music and audio analysis, other libraries like `PyAudio` for audio I/O, and `SoundFile` for reading and writing audio files, play crucial roles in the audio processing ecosystem. Here’s an integrated guide covering these libraries, highlighting their capabilities and common use cases.

### PyAudio - Audio I/O Interface

PyAudio provides Python bindings for PortAudio, the cross-platform audio I/O library, enabling users to easily use audio input and output devices.

#### Installation
```sh
pip install pyaudio
```
Note: Installing PyAudio might require additional dependencies on your system. Refer to the PyAudio documentation for platform-specific instructions.

#### Basic Usage

##### Playing Audio
```python
import pyaudio
import wave

filename = 'path/to/your/audio/file.wav'

# Open the file
wf = wave.open(filename, 'rb')

# Create a PyAudio interface
p = pyaudio.PyAudio()

# Open a stream to play audio
stream = p.open(format=p.get_format_from_width(wf.getsampwidth()),
                channels=wf.getnchannels(),
                rate=wf.getframerate(),
                output=True)

# Read data in chunks and play
data = wf.readframes(1024)
while data != b'':
    stream.write(data)
    data = wf.readframes(1024)

# Close the stream and PyAudio interface
stream.close()
p.terminate()
```

##### Recording Audio
```python
CHUNK = 1024
FORMAT = pyaudio.paInt16  # Depends on your needs
CHANNELS = 2
RATE = 44100  # Sampling rate
RECORD_SECONDS = 5
WAVE_OUTPUT_FILENAME = "output.wav"

p = pyaudio.PyAudio()

stream = p.open(format=FORMAT,
                channels=CHANNELS,
                rate=RATE,
                input=True,
                frames_per_buffer=CHUNK)

print("Recording...")

frames = []

for i in range(0, int(RATE / CHUNK * RECORD_SECONDS)):
    data = stream.read(CHUNK)
    frames.append(data)

print("Finished recording.")

# Stop and close the stream
stream.stop_stream()
stream.close()
# Terminate the PyAudio session
p.terminate()

# Save the recorded data as a WAV file
wf = wave.open(WAVE_OUTPUT_FILENAME, 'wb')
wf.setnchannels(CHANNELS)
wf.setsampwidth(p.get_sample_size(FORMAT))
wf.setframerate(RATE)
wf.writeframes(b''.join(frames))
wf.close()
```

### SoundFile - Reading and Writing Audio Files

`SoundFile` is a library for reading from and writing to audio files, such as WAV and FLAC, using data formats supported by libsndfile.

#### Installation
```sh
pip install SoundFile
```

#### Basic Usage

##### Reading an Audio File
```python
import soundfile as sf

data, samplerate = sf.read('path/to/your/audio/file.wav')
# `data` is a NumPy array containing the audio samples
# `samplerate` is the sampling rate of the audio file
```

##### Writing an Audio File
```python
sf.write('path/to/new/audio/file.wav', data, samplerate)
```

### Commonly Used Features Across Libraries

- **Audio Playback and Recording**: PyAudio provides low-level interfaces for audio playback and recording, ideal for applications requiring direct control over audio I/O.
- **Audio Analysis**: Libraries like Librosa are tailored for analyzing audio files, extracting features useful for music information retrieval, machine learning models, and more.
- **File Conversion and Processing**: SoundFile supports a wide range of audio formats, enabling easy conversion between them and manipulation of audio data.

### Potential Use Cases

- **Voice Recognition Systems**: Implementing systems that can recognize spoken commands or transcribe speech into text.
- **Music Genre Classification**: Developing algorithms to categorize music tracks into genres based on their audio features.
- **Sound Effect Generation**: Creating applications that generate sound effects or modify existing audio clips.
- **Audio Content Management**: Building tools for managing large audio datasets, including conversion, metadata tagging, and quality analysis.

### Integration and Workflow

A typical workflow might involve using PyAudio for capturing audio input from a microphone, processing or analyzing the audio with Librosa, and storing the processed audio using SoundFile. Each library addresses different aspects of audio handling in Python, providing a comprehensive toolkit for developers working on audio-related projects.

By leveraging these libraries in combination, developers can cover the entire spectrum of audio processing tasks, from real-time capture and playback to sophisticated analysis and feature extraction, facilitating the development of complex audio applications and systems.