Training LSTM network on raw audio data?
$begingroup$
I am trying to give an LSTM network raw audio data in forms of samples (44100 / second). Samples are defined in the [-1,1] value space. Currently I am giving it one sample for the Y values and the past N samples for X values.
Due to the fact that there are a lot of samples per second, you can see how it easily runs out of memory and the ability to give it large audio files (basically storing 16 samples for every sample given, for example will yield a very large dataset quickly).
I can post the code as well if necessary, however, I am only trying to figure out if my approach is correct. Training the data on a sine wave for example yields only values of 1, and the loss rate doesn't seem to go down much, so I am suspecting the way I am giving the network data is wrong. Is giving the past N samples to predict the current sample a good approach? I am pretty new in the AI field.
keras
asked 15 hours ago
Space GhostSpace Ghost
1
New contributor
Space Ghost is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
add a comment |
$begingroup$
I am trying to give an LSTM network raw audio data in forms of samples (44100 / second). Samples are defined in the [-1,1] value space. Currently I am giving it one sample for the Y values and the past N samples for X values.
Due to the fact that there are a lot of samples per second, you can see how it easily runs out of memory and the ability to give it large audio files (basically storing 16 samples for every sample given, for example will yield a very large dataset quickly).
I can post the code as well if necessary, however, I am only trying to figure out if my approach is correct. Training the data on a sine wave for example yields only values of 1, and the loss rate doesn't seem to go down much, so I am suspecting the way I am giving the network data is wrong. Is giving the past N samples to predict the current sample a good approach? I am pretty new in the AI field.
keras
asked 15 hours ago
Space GhostSpace Ghost
1
New contributor
Space Ghost is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
add a comment |
$begingroup$
I am trying to give an LSTM network raw audio data in forms of samples (44100 / second). Samples are defined in the [-1,1] value space. Currently I am giving it one sample for the Y values and the past N samples for X values.
Due to the fact that there are a lot of samples per second, you can see how it easily runs out of memory and the ability to give it large audio files (basically storing 16 samples for every sample given, for example will yield a very large dataset quickly).
I can post the code as well if necessary, however, I am only trying to figure out if my approach is correct. Training the data on a sine wave for example yields only values of 1, and the loss rate doesn't seem to go down much, so I am suspecting the way I am giving the network data is wrong. Is giving the past N samples to predict the current sample a good approach? I am pretty new in the AI field.
keras
asked 15 hours ago
Space GhostSpace Ghost
1
New contributor
Space Ghost is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
I am trying to give an LSTM network raw audio data in forms of samples (44100 / second). Samples are defined in the [-1,1] value space. Currently I am giving it one sample for the Y values and the past N samples for X values.
Due to the fact that there are a lot of samples per second, you can see how it easily runs out of memory and the ability to give it large audio files (basically storing 16 samples for every sample given, for example will yield a very large dataset quickly).
I can post the code as well if necessary, however, I am only trying to figure out if my approach is correct. Training the data on a sine wave for example yields only values of 1, and the loss rate doesn't seem to go down much, so I am suspecting the way I am giving the network data is wrong. Is giving the past N samples to predict the current sample a good approach? I am pretty new in the AI field.
keras
keras
asked 15 hours ago
Space GhostSpace Ghost
1
New contributor
Space Ghost is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 15 hours ago
Space GhostSpace Ghost
1
New contributor
Space Ghost is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 15 hours ago
Space GhostSpace Ghost
1
New contributor
Space Ghost is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 15 hours ago
Space GhostSpace Ghost
1
asked 15 hours ago
Space GhostSpace Ghost
1
1
New contributor
Space Ghost is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
Space Ghost is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
Space Ghost is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
add a comment |
add a comment |
0
active
oldest
votes
Your Answer
StackExchange.ready(function() {
var channelOptions = {
tags: "".split(" "),
id: "557"
};
initTagRenderer("".split(" "), "".split(" "), channelOptions);
StackExchange.using("externalEditor", function() {
// Have to fire editor after snippets, if snippets enabled
if (StackExchange.settings.snippets.snippetsEnabled) {
StackExchange.using("snippets", function() {
createEditor();
});
}
else {
createEditor();
}
});
function createEditor() {
StackExchange.prepareEditor({
heartbeatType: 'answer',
autoActivateHeartbeat: false,
convertImagesToLinks: false,
noModals: true,
showLowRepImageUploadWarning: true,
reputationToPostImages: null,
bindNavPrevention: true,
postfix: "",
imageUploader: {
brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
allowUrls: true
},
onDemand: true,
discardSelector: ".discard-answer"
,immediatelyShowMarkdownHelp:true
});
}
});
Space Ghost is a new contributor. Be nice, and check out our Code of Conduct.
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fdatascience.stackexchange.com%2fquestions%2f49324%2ftraining-lstm-network-on-raw-audio-data%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
0
active
oldest
votes
0
active
oldest
votes
active
oldest
votes
active
oldest
votes
Space Ghost is a new contributor. Be nice, and check out our Code of Conduct.
Space Ghost is a new contributor. Be nice, and check out our Code of Conduct.
Space Ghost is a new contributor. Be nice, and check out our Code of Conduct.
Space Ghost is a new contributor. Be nice, and check out our Code of Conduct.
Thanks for contributing an answer to Data Science Stack Exchange!
- Please be sure to answer the question. Provide details and share your research!
But avoid …
- Asking for help, clarification, or responding to other answers.
- Making statements based on opinion; back them up with references or personal experience.
Use MathJax to format equations. MathJax reference.
To learn more, see our tips on writing great answers.
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fdatascience.stackexchange.com%2fquestions%2f49324%2ftraining-lstm-network-on-raw-audio-data%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
