Exploring audio data augmentation – Labeling Audio Data-2
Zavia Dunlap
By using this noise-augmented audio data, the model accuracy increased from 0.946 to 0.964. Depending on the data, we can apply data augmentation and test the accuracy to decide whether…
Labeling the image data
Exploring audio data augmentation – Labeling Audio Data-1
Let’s see how to manipulate audio data by adding noise, using NumPy. Adding noise to audio data during training helps the model become more robust in real-world scenarios, where there…
IT Certification Exams
Labeling the image data
Labeling the video data
pyOpenAnnotate
Spectrogram visualization
Hands-on – labeling audio data using a CNN – Labeling Audio Data-3
Step 5: Train the model: This code initiates the training of the neural network model using the training data (X_train and y_train) for 20 epochs, with a batch size of…
Real-time voice classification with Random Forest – Labeling Audio Data-2
Combine and shuffle data: Positive and negative samples are combined into feature vectors (X) and corresponding labels (y). The data is shuffled to ensure a balanced distribution during training: Combine…
IT Certification Exams
Labeling the image data
Labeling the video data
Waveform visualization
Zero-crossing rate
Technical requirements – Labeling Audio Data
In this chapter, we will embark on this transformative journey through the realms of real-time audio capture, cutting-edge transcription with the Whisper model, and audio classification using a convolutional neural…
IT Certification Exams
Labeling the image data
Labeling the video data
pyOpenAnnotate
Spectrogram visualization
Troubleshooting common issues during data analysis – Exploring Audio Data
Troubleshooting common issues during audio data analysis involves identifying and addressing problems that may arise at various stages of the analysis pipeline. Here are some common issues and guidance on…
Recent advances in audio data analysis – Exploring Audio Data
Audio data analysis is a rapidly evolving field, and recent developments include advancements in deep learning models, transfer learning, and the application of neural networks to various audio tasks. Here…
IT Certification Exams
Labeling the image data
Labeling the video data
Waveform visualization
Zero-crossing rate
Waveform visualization – Exploring Audio Data
Visualizing audio data with matplotlib and Librosa Visualizations play a crucial role in understanding and interpreting audio data. Here’s a comparison of different types of visualizations for audio data and…
Zero-crossing rate – Exploring Audio Data
The zero-crossing rate measures how rapidly the signal changes from positive to negative or vice versa. It’s often used to characterize noisiness in audio. Here’s how you can calculate it:…