PHP Master | Extract an Excerpt from a WAV File
While PHP is known for building web pages and applications, it has much more than that. I recently needed to dynamically extract an audio from a WAV file and allow the user to download it through the browser. I tried to find a library that suited my needs, but I didn't succeed and had to write my own code. This is a great opportunity to dig into WAV file structure. In this post, I will briefly outline the WAV file format and explain the library I developed: Audero Wav Extractor.
Key Points
- Waveform Audio File Format (WAV) is a standard used by Microsoft to store digital audio data and consists of blocks representing different parts of an audio file. "RIFF", "Fmt" and "Data" are the most important blocks.
- Audero Wav Extractor is a PHP library that allows extracting fragments from WAV files. It requires PHP 5.3 or later, and can save the fragment to the local hard drive, download it through the user's browser, or return it as a string for later processing. The
- The Audero Wav Extractor library contains methods such as
downloadChunk()
,saveChunk()
, andgetChunk()
to manage the extraction process. Each method requires extracting the start and end time parameters of the fragment. - The duration of the WAV file can be calculated using the following formula: <code>time = dataChunkSize / (sampleRate * channelsNumber * bitsPerSample / 8)</code>. This information, along with other important data, can be retrieved from the "Data" and "Fmt" blocks of the WAV file.
WAV format overview
Wave audio file format, also known as WAVE or WAV, is the file format standard used by Microsoft to store digital audio data. A WAV file consists of a set of different types of blocks that represent different parts of the audio file. You can think of this format as an HTML page: the first block is like the <section></section>
part of the web page, so in it you can find several pieces of information about the file itself, while the block containing the audio data itself is located at the Part. In this case, "block" refers to the portion of data contained in the file. The most important format block is "RIFF", which contains the number of bytes of the file; "Fmt", which contains important information such as the sampling rate and channel number; and "Data", which actually contains audio stream data. Each block must have at least two fields: id and size. In addition, each valid WAV must have at least two blocks: Fmt and Data. The first one is usually at the beginning of the file, but after RIFF. Each block has its own format and field, and one field forms a sub-part of the block. The WAV format was not fully specified in the past, which causes the file to have headers that do not strictly follow the rules. So when you work on audio, you may find that a file has one or more fields, and even the most important fields are set to zero or wrong values. To give you an idea of what is inside a block, the first block of each WAV file is RIFF. The first 4 bytes contain the string "RIFF", and the next 4 bytes contain the file size minus the 8 bytes used by these two data parts. The last 4 bytes of the RIFF block contain the string "WAVE". You may guess what the purpose of this data is. In this case, you can use them to identify whether the file you are parsing is actually a WAV file, like I did in the <section></section>
method of the library's Wav class. Another interesting thing to explain is how to calculate the duration of a WAV file. All the information you need can be retrieved from the two necessary blocks mentioned earlier, namely: data block size, sampling rate, number of channels, and number of bits per sample. The formula for calculating file time (in seconds) is as follows: setFilePath()
<code>time = dataChunkSize / (sampleRate * channelsNumber * bitsPerSample / 8)</code>
<code>dataChunkSize = 4498170 sampleRate = 22050 channelsNumber = 16 bitsPerSample = 1</code>
<code>time = 4498170 / (22050 * 1 * 16 / 8)</code>
- https://www.php.cn/link/21c1da87c1afdd4ed2836bdb521bea78
- https://www.php.cn/link/3493d96f8fcb16313a77ecfd294734c9
What is Audero Wav Extractor
Audero Wav Extractor is a PHP library that allows you to extract fragments from WAV files. You can save the extracted fragment to your local hard drive, download it through the user's browser, or return it as a string for later processing. The only special requirement for this library is PHP 5.3 or later because it uses a namespace. All classes of the library are in the WavExtractor directory, but you will notice that there is an additional Loader directory where you can find the library's autoloader. The developer's entry point is the AuderoWavExtractor class, which has three main methods in the project:
-
downloadChunk()
: Download the clip -
saveChunk()
: Save it to the hard drive -
getChunk()
: Search the fragment as a string
The first two parameters of all these methods are the same: $start
and $end
, which represent the start and end times (in milliseconds) of the portion to be extracted, respectively. Additionally, downloadChunk()
and saveChunk()
accept an optional third parameter to set the name of the extracted fragment. If no name is provided, the method generates a name itself in the format "InputFilename-Start-End.wav". In the WavExtractor directory, there are two subfolders: Utility, which contains the Converter class with certain utility methods; and Wav. The latter contains the Wav, Chunk, and ChunkField classes. The first one, as you might expect, represents a WAV file, which consists of one or more blocks (Chunk type). This class allows you to retrieve WAV headers, audio durations, and some other useful information. Its most important method is getWavChunk()
, which retrieves the specified audio part by reading bytes in the file. The Chunk class represents a block of a WAV file that is extended by a dedicated class contained in the Chunk folder. The latter does not support all existing block types, only the most important block types. The unidentified part is managed by the general class and is simply ignored throughout the process. The last class described is ChunkField. As I pointed out, each block has its own type and field, and each field has a different length (in bytes) and format. This is a very important message because you need to pass the correct parameters to correctly parse bytes using PHP's pack()
and unpack()
functions, otherwise you will receive an error. To help manage the data, I decided to wrap them into a class that holds the format, size, and values of each field.
How to use Audero Wav Extractor
You can get the "Audero Wav Extractor" through Composer, add the following lines to your composer.json
file and run its installation command:
<code>time = dataChunkSize / (sampleRate * channelsNumber * bitsPerSample / 8)</code>
Composer will download and place the library in the vendor/audero
directory of the project. Alternatively, you can download the library directly from its repository. To extract the fragment and force download to the user's browser, you will write a code similar to the following:
<code>time = dataChunkSize / (sampleRate * channelsNumber * bitsPerSample / 8)</code>
In the first line, I included the Composer autoloader and then set the value I'm going to use. As you can see, I provide the source file, the output path including the file name, and the time range I want to extract. Then I created an instance of AuderoWavExtractor, took the source file as a parameter, and called the downloadChunk()
method. Note that because the output path is passed by reference, you always need to set it as a variable. Let's look at another example. I'll show you how to select a time range and save the file to your local hard drive. Also, I will use the autoloader included in the project.
<code>dataChunkSize = 4498170 sampleRate = 22050 channelsNumber = 16 bitsPerSample = 1</code>
Apart from the loader configuration, this code snippet is very similar to the previous code snippet. In fact, I only made two changes: the first is the method called, saveChunk()
instead of downloadChunk()
, and the second is that I did not set the output file name (it will use the default format explained earlier).
Conclusion
In this post, I show you "Audero Wav Extractor" and how to easily extract one or more fragments from a given WAV file. I wrote the library for a working project that requires a very narrow set of tiles, so if the WAV or its header is severely corrupted, the library may fail, but I wrote the code to try to where possible Recover from the error. Feel free to use the demos and files contained in the repository, as I have released it under the CC BY-NC 3.0 license.
(The following is a pseudo-original work in the original FAQ part, which maintains the original meaning and adjusts the language)
FAQs (FAQ) on Extracting Fragments from WAV Files
How to extract specific parts of a WAV file?
To extract specific parts of a WAV file, you need to use an audio editing software like Audacity. Open the WAV file in Audacity, use the selection tool to select the section you want to extract, and then select Export Selection from the File menu. You can then save the selected portion as a new WAV file.
Can I extract data from WAV files in a programming language?
Yes, you can extract data from WAV files using a programming language like Python. Libraries such as scipy.io.wavfile
and wave
can be used to read WAV files and extract data. You can then operate this data according to your needs.
How to extract secret information from audio files?
Extracting secret information from an audio file involves a process called steganography. This process involves hiding information in non-secret text or data. There are various software and tools that can help you extract hidden messages from audio files.
Can I extract a voice or a voice from a WAV file?
Extracting a sound from a WAV file is a complex task that involves audio source separation or speech separation. This can be achieved using advanced signal processing techniques and machine learning algorithms. Software like Audacity can help to some extent, but for more complex tasks you may need to use more advanced tools or services.
Which function in R extracts dB values from a WAV file?
In R, you can use the tuneR package to read WAV files and extract data. The readWave()
function can be used to read a WAV file, and the generated object can be used to access dB values. However, you may need to convert the amplitude value to dB using the appropriate mathematical formula.
How to extract frequency information from WAV files?
Extracting frequency information from a WAV file involves performing a Fourier transform on the data. This can be done using the numpy library in Python or the fft library in R. The results of the Fourier transform will give you the frequency components of the audio signal.
Can I extract metadata from WAV files?
Yes, you can extract metadata from WAV files. This may include information such as sampling rate, bit depth, number of channels and duration. This can be done using audio processing libraries in various programming languages.
How to extract multiple parts from a WAV file?
To extract multiple parts from a WAV file, you can use audio editing software like Audacity. You can select each part you want to extract and export it as a new file. This process can be repeated for each part to be extracted.
Can I extract audio from a video file and save it as a WAV file?
Yes, you can extract audio from a video file and save it as a WAV file. This can be done using video editing software or conversion tools. This process involves opening a video file, extracting an audio track, and saving it as a WAV file.
How to convert a WAV file to another audio format?
To convert a WAV file to another audio format, you can use audio conversion software or tools. These tools allow you to open a WAV file and save it in another format, such as MP3, FLAC, or AAC. The conversion process usually involves selecting the output format and setting the required mass or bit rate.
The above is the detailed content of PHP Master | Extract an Excerpt from a WAV File. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics

Alipay PHP...

JWT is an open standard based on JSON, used to securely transmit information between parties, mainly for identity authentication and information exchange. 1. JWT consists of three parts: Header, Payload and Signature. 2. The working principle of JWT includes three steps: generating JWT, verifying JWT and parsing Payload. 3. When using JWT for authentication in PHP, JWT can be generated and verified, and user role and permission information can be included in advanced usage. 4. Common errors include signature verification failure, token expiration, and payload oversized. Debugging skills include using debugging tools and logging. 5. Performance optimization and best practices include using appropriate signature algorithms, setting validity periods reasonably,

Session hijacking can be achieved through the following steps: 1. Obtain the session ID, 2. Use the session ID, 3. Keep the session active. The methods to prevent session hijacking in PHP include: 1. Use the session_regenerate_id() function to regenerate the session ID, 2. Store session data through the database, 3. Ensure that all session data is transmitted through HTTPS.

The enumeration function in PHP8.1 enhances the clarity and type safety of the code by defining named constants. 1) Enumerations can be integers, strings or objects, improving code readability and type safety. 2) Enumeration is based on class and supports object-oriented features such as traversal and reflection. 3) Enumeration can be used for comparison and assignment to ensure type safety. 4) Enumeration supports adding methods to implement complex logic. 5) Strict type checking and error handling can avoid common errors. 6) Enumeration reduces magic value and improves maintainability, but pay attention to performance optimization.

The application of SOLID principle in PHP development includes: 1. Single responsibility principle (SRP): Each class is responsible for only one function. 2. Open and close principle (OCP): Changes are achieved through extension rather than modification. 3. Lisch's Substitution Principle (LSP): Subclasses can replace base classes without affecting program accuracy. 4. Interface isolation principle (ISP): Use fine-grained interfaces to avoid dependencies and unused methods. 5. Dependency inversion principle (DIP): High and low-level modules rely on abstraction and are implemented through dependency injection.

How to debug CLI mode in PHPStorm? When developing with PHPStorm, sometimes we need to debug PHP in command line interface (CLI) mode...

Sending JSON data using PHP's cURL library In PHP development, it is often necessary to interact with external APIs. One of the common ways is to use cURL library to send POST�...

Static binding (static::) implements late static binding (LSB) in PHP, allowing calling classes to be referenced in static contexts rather than defining classes. 1) The parsing process is performed at runtime, 2) Look up the call class in the inheritance relationship, 3) It may bring performance overhead.
