How to extract and quantify tone information from an audio file using Tone.js?

Analyze audio and quantize tones with Tone.js

In audio analysis, it is crucial to extract and quantify tone information, which is widely used in music analysis, audio processing and other fields. This article will demonstrate how to extract tone information from MP3 or WAV audio files using the Tone.js library and convert it into a series of numerical values ​​(for example: 3, 3, 9, 2, 10, 13), indicating how the tone changes over time.

First, we need a sample program to show the extraction of audio spectrum information. Through the visual spectrum diagram, we can observe the frequency components of the audio. After extracting spectrum information, the key is to map the frequency value to the specific tone value.

Tones are usually represented by pronunciation names (for example: "C", "C#", "D", "D#", "E"). We convert the frequency value to the corresponding tone name to achieve quantification of tones. For example, a specific frequency may correspond to the pronunciation name "C" and another frequency may correspond to "D#".

In actual operations, you need to pay attention to memory management. If you encounter a lack of memory problem (for example, in the sample program), you can try refreshing the page to free up the resource.

Finally, we will get a sequence of numerical values ​​representing the tone of the audio file over time, one value per second. This method is suitable for a variety of audio formats, including MP3 and WAV.

The above is the detailed content of How to extract and quantify tone information from an audio file using Tone.js?. For more information, please follow other related articles on the PHP Chinese website!