网络音频 API 播放时通过 http 流式传输音频标签输出
Web Audio API stream audio tags output via http as they are played
我正在开发一个 Electron 应用程序,它通过 Telegram Bot Api 接口接收 song/voice 请求,并以 jukebox/radio 方式在音频对象中播放它们。
我想要实现的是通过 http 将我的应用程序的音频输出实时流式传输到连接到本地 (nodejs) 服务器的客户端。
所以基本上我需要在播放时处理所有音频标签 PCM,然后将它们混合(也许将结果转换为 mp3 格式?)并将结果通过管道传输给客户端。至少这是我目前的想法。
不幸的是,我一直停留在捕获音频对象输出上。
我了解了 RecordJs 以及它如何从 AudioNode 对象录制音频,但我还没有找到混合多个音频标签传出流的示例。
你能帮我解决这个问题吗?
当网络音频 API 呈现时,音频是原始 PCM(未压缩),它在内存缓冲区中可用,根据缓冲区分配的大小获得 emptied/reloaded - 您可以拦截并复制此缓冲区进入下游发布给客户的流程
将以下代码保存为 html 文件,然后在同一目录中使用
提供它
python -m SimpleHTTPServer
将浏览器指向 http://localhost:8000/
并选择你的新 html 文件......浏览器必须提示确认使用麦克风......然后查看你的 javascript 控制台(ctrl-shift-i)......在这里你看到第一个三个FFT 和时域音频数组缓冲区的元素...在
上的代码搜索中
array_time_domain
这是您的原始 PCM 音频(将被复制并发送给订阅的客户端(留作 reader 的练习 ;-))...如果不需要降低 FFT 相关代码,请注释掉CPU/battery 流失
注意 - onaudioprocess 回调会随着音频的传输而重复调用,因此请确保您上面提到的复制过程非常高效,因此它比音频缓冲区刷新之间的循环周期更快地完成(提示 Web Worker)
这里我使用来自麦克风的输入源音频。无论源音频如何,此内部回调渲染事件循环都是相同的
<html><head><meta http-equiv="Content-Type" content="text/html; charset=ISO-8859-1">
<title>capture microphone then show time & frequency domain output</title>
<script type="text/javascript">
var webaudio_tooling_obj = function () {
var audioContext = new AudioContext();
console.log("audio is starting up ...");
var BUFF_SIZE_RENDERER = 16384;
var SIZE_SHOW = 3; // number of array elements to show in console output
var audioInput = null,
microphone_stream = null,
gain_node = null,
script_processor_node = null,
script_processor_analysis_node = null,
analyser_node = null;
if (!navigator.getUserMedia)
navigator.getUserMedia = navigator.getUserMedia || navigator.webkitGetUserMedia ||
navigator.mozGetUserMedia || navigator.msGetUserMedia;
if (navigator.getUserMedia){
navigator.getUserMedia({audio:true},
function(stream) {
start_microphone(stream);
},
function(e) {
alert('Error capturing audio.');
}
);
} else { alert('getUserMedia not supported in this browser.'); }
// ---
function show_some_data(given_typed_array, num_row_to_display, label) {
var size_buffer = given_typed_array.length;
var index = 0;
console.log("__________ " + label);
if (label === "time") {
for (; index < num_row_to_display && index < size_buffer; index += 1) {
var curr_value_time = (given_typed_array[index] / 128) - 1.0;
console.log(curr_value_time);
}
} else if (label === "frequency") {
for (; index < num_row_to_display && index < size_buffer; index += 1) {
console.log(given_typed_array[index]);
}
} else {
throw new Error("ERROR - must pass time or frequency");
}
}
function process_microphone_buffer(event) {
var i, N, inp, microphone_output_buffer;
microphone_output_buffer = event.inputBuffer.getChannelData(0); // just mono - 1 channel for now
}
function start_microphone(stream){
gain_node = audioContext.createGain();
gain_node.connect( audioContext.destination );
microphone_stream = audioContext.createMediaStreamSource(stream);
microphone_stream.connect(gain_node);
script_processor_node = audioContext.createScriptProcessor(BUFF_SIZE_RENDERER, 1, 1);
script_processor_node.onaudioprocess = process_microphone_buffer;
microphone_stream.connect(script_processor_node);
// --- enable volume control for output speakers
document.getElementById('volume').addEventListener('change', function() {
var curr_volume = this.value;
gain_node.gain.value = curr_volume;
console.log("curr_volume ", curr_volume);
});
// --- setup FFT
script_processor_analysis_node = audioContext.createScriptProcessor(2048, 1, 1);
script_processor_analysis_node.connect(gain_node);
analyser_node = audioContext.createAnalyser();
analyser_node.smoothingTimeConstant = 0;
analyser_node.fftSize = 2048;
microphone_stream.connect(analyser_node);
analyser_node.connect(script_processor_analysis_node);
var buffer_length = analyser_node.frequencyBinCount;
var array_freq_domain = new Uint8Array(buffer_length);
var array_time_domain = new Uint8Array(buffer_length);
console.log("buffer_length " + buffer_length);
script_processor_analysis_node.onaudioprocess = function() {
// get the average for the first channel
analyser_node.getByteFrequencyData(array_freq_domain);
analyser_node.getByteTimeDomainData(array_time_domain);
// draw the spectrogram
if (microphone_stream.playbackState == microphone_stream.PLAYING_STATE) {
show_some_data(array_freq_domain, SIZE_SHOW, "frequency");
show_some_data(array_time_domain, SIZE_SHOW, "time"); // store this to record to aggregate buffer/file
}
};
}
}(); // webaudio_tooling_obj = function()
</script>
</head>
<body>
<p>Volume</p>
<input id="volume" type="range" min="0" max="1" step="0.1" value="0.0"/>
</body>
</html>
我正在开发一个 Electron 应用程序,它通过 Telegram Bot Api 接口接收 song/voice 请求,并以 jukebox/radio 方式在音频对象中播放它们。
我想要实现的是通过 http 将我的应用程序的音频输出实时流式传输到连接到本地 (nodejs) 服务器的客户端。
所以基本上我需要在播放时处理所有音频标签 PCM,然后将它们混合(也许将结果转换为 mp3 格式?)并将结果通过管道传输给客户端。至少这是我目前的想法。
不幸的是,我一直停留在捕获音频对象输出上。 我了解了 RecordJs 以及它如何从 AudioNode 对象录制音频,但我还没有找到混合多个音频标签传出流的示例。
你能帮我解决这个问题吗?
当网络音频 API 呈现时,音频是原始 PCM(未压缩),它在内存缓冲区中可用,根据缓冲区分配的大小获得 emptied/reloaded - 您可以拦截并复制此缓冲区进入下游发布给客户的流程
将以下代码保存为 html 文件,然后在同一目录中使用
提供它python -m SimpleHTTPServer
将浏览器指向 http://localhost:8000/ 并选择你的新 html 文件......浏览器必须提示确认使用麦克风......然后查看你的 javascript 控制台(ctrl-shift-i)......在这里你看到第一个三个FFT 和时域音频数组缓冲区的元素...在
上的代码搜索中array_time_domain
这是您的原始 PCM 音频(将被复制并发送给订阅的客户端(留作 reader 的练习 ;-))...如果不需要降低 FFT 相关代码,请注释掉CPU/battery 流失
注意 - onaudioprocess 回调会随着音频的传输而重复调用,因此请确保您上面提到的复制过程非常高效,因此它比音频缓冲区刷新之间的循环周期更快地完成(提示 Web Worker)
这里我使用来自麦克风的输入源音频。无论源音频如何,此内部回调渲染事件循环都是相同的
<html><head><meta http-equiv="Content-Type" content="text/html; charset=ISO-8859-1">
<title>capture microphone then show time & frequency domain output</title>
<script type="text/javascript">
var webaudio_tooling_obj = function () {
var audioContext = new AudioContext();
console.log("audio is starting up ...");
var BUFF_SIZE_RENDERER = 16384;
var SIZE_SHOW = 3; // number of array elements to show in console output
var audioInput = null,
microphone_stream = null,
gain_node = null,
script_processor_node = null,
script_processor_analysis_node = null,
analyser_node = null;
if (!navigator.getUserMedia)
navigator.getUserMedia = navigator.getUserMedia || navigator.webkitGetUserMedia ||
navigator.mozGetUserMedia || navigator.msGetUserMedia;
if (navigator.getUserMedia){
navigator.getUserMedia({audio:true},
function(stream) {
start_microphone(stream);
},
function(e) {
alert('Error capturing audio.');
}
);
} else { alert('getUserMedia not supported in this browser.'); }
// ---
function show_some_data(given_typed_array, num_row_to_display, label) {
var size_buffer = given_typed_array.length;
var index = 0;
console.log("__________ " + label);
if (label === "time") {
for (; index < num_row_to_display && index < size_buffer; index += 1) {
var curr_value_time = (given_typed_array[index] / 128) - 1.0;
console.log(curr_value_time);
}
} else if (label === "frequency") {
for (; index < num_row_to_display && index < size_buffer; index += 1) {
console.log(given_typed_array[index]);
}
} else {
throw new Error("ERROR - must pass time or frequency");
}
}
function process_microphone_buffer(event) {
var i, N, inp, microphone_output_buffer;
microphone_output_buffer = event.inputBuffer.getChannelData(0); // just mono - 1 channel for now
}
function start_microphone(stream){
gain_node = audioContext.createGain();
gain_node.connect( audioContext.destination );
microphone_stream = audioContext.createMediaStreamSource(stream);
microphone_stream.connect(gain_node);
script_processor_node = audioContext.createScriptProcessor(BUFF_SIZE_RENDERER, 1, 1);
script_processor_node.onaudioprocess = process_microphone_buffer;
microphone_stream.connect(script_processor_node);
// --- enable volume control for output speakers
document.getElementById('volume').addEventListener('change', function() {
var curr_volume = this.value;
gain_node.gain.value = curr_volume;
console.log("curr_volume ", curr_volume);
});
// --- setup FFT
script_processor_analysis_node = audioContext.createScriptProcessor(2048, 1, 1);
script_processor_analysis_node.connect(gain_node);
analyser_node = audioContext.createAnalyser();
analyser_node.smoothingTimeConstant = 0;
analyser_node.fftSize = 2048;
microphone_stream.connect(analyser_node);
analyser_node.connect(script_processor_analysis_node);
var buffer_length = analyser_node.frequencyBinCount;
var array_freq_domain = new Uint8Array(buffer_length);
var array_time_domain = new Uint8Array(buffer_length);
console.log("buffer_length " + buffer_length);
script_processor_analysis_node.onaudioprocess = function() {
// get the average for the first channel
analyser_node.getByteFrequencyData(array_freq_domain);
analyser_node.getByteTimeDomainData(array_time_domain);
// draw the spectrogram
if (microphone_stream.playbackState == microphone_stream.PLAYING_STATE) {
show_some_data(array_freq_domain, SIZE_SHOW, "frequency");
show_some_data(array_time_domain, SIZE_SHOW, "time"); // store this to record to aggregate buffer/file
}
};
}
}(); // webaudio_tooling_obj = function()
</script>
</head>
<body>
<p>Volume</p>
<input id="volume" type="range" min="0" max="1" step="0.1" value="0.0"/>
</body>
</html>