speech-recognition | End to End Speech Recognition with Tensorflow | Speech library
kandi X-RAY | speech-recognition Summary
kandi X-RAY | speech-recognition Summary
End to End Speech Recognition implemented with deep learning framework Tensorflow. Build upon Recurrent Neural Networks with LSTM and CTC(Connectionist Temporal Classification).
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Top functions reviewed by kandi - BETA
- Train the LSTM network
- Gets the decoder
- Calculate ctc_loss
- Compute the label error rate
- Train the model
- Returns the next step
- Log progress information
- Loads a trained model
- Build the model
- Returns the number of classes
- The number of hidden outputs
- Predict using LSTMCTC
- Preprocess a WAV file
- Predict function
- Return the number of speakers
- The feature size
- Number of contexts
- Returns a test dataset
- Absolute path of the dataset
- Test test
- Generate test dataset
- Runs the test step
- Return a list of removed transcripts
- Construct a tf Tensor from sequences
- Train a single epoch
- Show speech
speech-recognition Key Features
speech-recognition Examples and Code Snippets
Community Discussions
Trending Discussions on speech-recognition
QUESTION
Hi guys i want to make speech to text in React component. But when i run it I get this error:
react_speech_recognition__WEBPACK_IMPORTED_MODULE_1___default(...) is not a function
Can someone show me what to do?
ANSWER
Answered 2021-Jun-02 at 11:29It is because of this line SpeechRecognition(Mic)
. The Error states that the default export from your module is not a function which means that SpeechRecognition
is not a function so you cannot call it .
change your code as
QUESTION
Goal
I am aiming to get the transcript
value, from the function Dictaphone and pass it into to the SearchBar class, and finally set the state term
to transcript
.
Current code
...ANSWER
Answered 2021-Apr-24 at 22:43useSpeechRecognition
is a React hook, which is a special type of function that only works in specific situations. You can't use hooks inside a class-based component; they only work in function-based components, or in custom hooks. See the rules of hooks for all the limitations.
Since this hook is provided by a 3rd party library, you have a couple of options. One is to rewrite your search bar component to be a function. This may take some time if you're unfamiliar with hooks.
You can also see if the react-speech-recognition
library provides any utilities that are intended to work with class-based components.
QUESTION
I'm trying to generate timestamps using Azure S2T in C#. I've tried the following resources:
How to get Word Level Timestamps using Azure Speech to Text and the Python SDK?
How to generate timestamps in speech recognition?
The second has been the most helpful, but I'm still getting errors. My code is:
...ANSWER
Answered 2021-Mar-31 at 05:24You should use
QUESTION
My company serves e-learning lessons through HTML5 files created in H5P, Captivate, Storyline. These lessons use xAPI to communicate grades and user information to an LRS. Recently I have been working on implementing voice recognition into these lessons using either Web speech API or Annyang and eventually we would like to build our own proprietary speech API. However, I see that voice recognition only seems to be compatible with Chrome desktop right now. I am working on creating a mobile app using React Native that can access a user's lessons from the database and "play" them in an in-app browser. So my questions are as follows:
- Would it be possible to hand-roll an in-app browser like Capacitor/ Cordova/ some other IAB to support the W3C Web Speech API specification?
- Would it even be allowed? Would Apple allow an app with such an IAB in their app store?
- Am I correct in understanding that an in-app browser could still support the necessary Javascript for features like xAPI, drag and drop, and session progress saving? Or am I barking up the wrong tree entirely?
ANSWER
Answered 2021-Mar-01 at 14:18- Which Speech API's? The spec you referenced is broad and includes a number of underlying API's which are supported across different platforms.
- Probably not. Many apps submitted this way get rejected. Apple is against the method you're trying to load the app. An app that simply loads an IAB is not really an app to Apple.
2.5.2: Apps should be self-contained in their bundles, and may not read or write data outside the designated container area...
- IAB is a hit or miss. They can't access native features through plugins. It should support most web standards, but from my experience, they're use for simpler use cases. Not hosting feature rich apps. Why not make a regular Cordova/Capacitor app without the IAB?
QUESTION
I'm new to TensorFlow and python. I'm trying to run and learn "the Speech Recognition using Keras" in https://www.kaggle.com/sunyuanxi/speech-recognition-keras and I have a problem with this part of the code below and cant debug the error. I really need you to help me. thank you
...ANSWER
Answered 2020-Dec-23 at 10:49On windows, the path separator is '\' not '/'. Try to use:
QUESTION
So i tried to create a speech recognition neural network using the librispeech dataset dev-clean. I tried to convert the code from https://github.com/soheil-mpg/Speech-Recognition into a jupyter notebook.
Everything appears to be working. The model can be trained and doesn't give any errors. But when using model.predict() i get the following error:
AssertionError: Could not compute output Tensor("ctc/ExpandDims_22:0", shape=(None, 1), dtype=float32)
I uploaded the Jupyter Notebook to https://github.com/jake-salmone/ASR
The code is almost identical, the only thing i have change is, that i don't use the json, but use a pandas DataFrame.
...ANSWER
Answered 2020-Nov-19 at 22:09I found the answer!: The model has the wrong output-dimensions.
Of course the ctc loss should only be added to the model during training.
when adding the ctc loss, it should only happen within the scope of a function:
QUESTION
I'm trying to use TensorFlow Lite for a voice recognition project using Jupyter notebook but when I try to do a "import librosa" (using commands found here: https://github.com/ShawnHymel/tflite-speech-recognition/blob/master/01-speech-commands-mfcc-extraction.ipynb) I keep getting this error:
...ANSWER
Answered 2020-Dec-15 at 19:51Install sndfile for your operating system. On CentOS that should be yum install libsndfile
.
QUESTION
I am trying to run a model that was trained with MFCC's and the Google Speech Dataset. The model was trained Here using the first 2 jupyter notebooks.
Now, I am trying to implement it onto a Raspberry Pi with Tensorflow 1.15.2, note that it was also trained in TF 1.15.2. The model loads and I get a correct model.summary():
...ANSWER
Answered 2020-Dec-09 at 22:39Turns out we needed to create MFCCs with Python_Speech_features. This provided us the 1,16,16, then we expanded dimensions for 1,16,16,1.
QUESTION
as stated in the title of the question - What technologies I may use to write drum-pattern audio signal based recognition program? I want to create a tool for me as a drummer musician to transcribe a drum-part from a record. I imagine this as similiar technology to speech-recog but made especially for drum patterns previously defined in some kind of a drum pattern base. The problem is Im a very beginner in programming. For half year i was interested in microcontrollers with basic c++, not even OOP. Currently im trying out python and this is my final programming knowledge/experience background. Now because of that poor level of know-how in IT, I dont really know what technology, frameworks etc I should get interested in with this kind of a project. It may be obvious that I should look for speech-recognition technologies and learn that and then apply that knowledge to build my own program, but Im not really sure where is the best place to start and if im ready for reading heavy walls of professsional open source projects code. Maybe there is some kind of a friendly python framework to get me started in that topic? I found Python Librosa framework in my research but it seems really advanced and it looks like i should learn signal-theory to get fluent in using that. Let me know what do you think and what kind of tactic should i aim to in your opinion.
...ANSWER
Answered 2020-Nov-16 at 12:50The task of transcribing music automatically, from audio into notes (typically MIDI), is known in the research community as Automatic Music Transcription. The specialized task of doing it on drums only is known as Automatic Drum Transcription (ADT).
ADT is widely researched, and both open-source and commercial solutions are available. One open-source software can be found in ADTLib. It provides a very simple Python API that takes a WAV file and returns transcribed drum track. There are papers linked in the README file, describing how it is put together. A web-based tool called ADTWeb allows to try out transcribing drums without installing any software.
Note that ADT usually assumes an input that is only/predominantly drums. If you want to extract drum patterns from a mixed song containing also other instruments, you mayb need some kind of Source Separation step as well.
QUESTION
Last year, apple released on-device speech recognition starting with iOS 13. I've been playing with it and I haven't been able to get it to work on any of the simulators. The only way that it works is if I plug in an actual device. Is this how it's expected to be?
This is strongly influenced by this question. I have tried the answer on all of the simulators and it is stuck on downloading: "This Siri voice will take effect when downloaded"
Sample code can be found here. I've modified it with the below block:
...ANSWER
Answered 2020-Nov-12 at 11:19Yes indeed. You must use physical device for speech recognition support. You must use microphone input which is not supported in the simulator. It is quite common for some capabilities to not be supported in the simulator. Specifically voice relate. link
In the WWDC video they also mentioned all supported devices (you must have A9 core).
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