Sphinx4 tutorial

Hello I am new to sphinx and I want to build a speech recognition for Hindi language. It contains acoustic and language model as well as dictionary file. I am currently working on windows machin.

Can anyone pls help me on how to implement these models into program. I have read the tutorials but I couldn't get through. Any help would save a lot of time of mine. Thanks in advance.

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Also, hindi model is very old and not very good. Nickolay I tried the above. I am getting error in importing configuration, speechResult and StreamSpeechRecognizer. Could you share the details of how you solved this? That'd help make this thread valuable to others struggling with something similar.

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IT Management. Project Management. Services Business VoIP. Resources Blog Articles Deals. Menu Help Create Join Login. Getting started withSphinx4 for Hindi language. Forum: Sphinx4 Help.The language model is an important component of the configuration which tells the decoder which sequences of words are possible to recognize. There are several types of models: keyword lists, grammars and statistical language models and phonetic language models. They have different capabilities and performance properties.

You can chose any decoding mode according to your needs and you can even switch between modes in runtime. See the Pocketsphinx tutorial for more details. Pocketsphinx supports a keyword spotting mode where you can specify a list of keywords to look for.

The advantage of this mode is that you can specify a threshold for each keyword so that keywords can be detected in continuous speech. All other modes will try to detect the words from a grammar even if you used words which are not in the grammar. A typical keyword list looks like this:. The threshold must be specified for every keyphrase. For shorter keyphrases you can use smaller thresholds like 1e-1for longer keyphrases the threshold must be bigger, up to 1e If your keyphrase is very long — larger than 10 syllables — it is recommended to split it and spot for parts separately.

The threshold must be tuned to balance between false alarms and missed detections. The best way to do this is to use a prerecorded audio file. The common tuning process is the following:. The command will print many lines, some of them are keywords with detection times and confidences.

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For the best accuracy it is better to have a keyphrase with syllables. Too short phrases are easily confused. To use keyword list in the command line specify it with the -kws option. You can also use a -keyphrase option to specify a single keyphrase.In this tutorial, you will learn to handle a complete state-of-the-art HMM-based speech recognition system.

An HMM-based system, like all other speech recognition systems, functions by first learning the characteristics or parameters of a set of sound units, and then using what it has learned about the units to find the most probable sequence of sound units for a given speech signal.

The process of learning about the sound units is called training. The process of using the knowledge acquired to deduce the most probable sequence of units in a given signal is called decodingor simply recognition. You will be given instructions on how to download, compile, and run the components needed to build a complete speech recognition system.

Please check a CMUSphinx project page for more details on available decoders and their applications. This tutorial does not instruct you on how to build a language model, but you can check the CMU SLM Toolkit page for an excellent manual.

At the end of this tutorial, you will be in a position to train and use this system for your own recognition tasks. More importantly, through your exposure to this system, you will have learned about several important issues involved in using a real HMM-based ASR system. The internal, csh-based Robust tutorial is still available, though its use is discouraged. The SPHINX trainer consists of a set of programs, each responsible for a well defined task, and a set of scripts that organizes the order in which the programs are called.

sphinx4 tutorial

You have to compile the code in your favorite platform. The trainer learns the parameters of the models of the sound units using a set of sample speech signals. This is called a training database. A choice of training databases will also be provided to you.

The trainer also needs to be told which sound units you want it to learn the parameters of, and at least the sequence in which they occur in every speech signal in your training database. This information is provided to the trainer through a file called the transcript filein which the sequence of words and non-speech sounds are written exactly as they occurred in a speech signal, followed by a tag which can be used to associate this sequence with the corresponding speech signal.

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The trainer then looks into a dictionary which maps every word to a sequence of sound units, to derive the sequence of sound units associated with each signal. Thus, in addition to the speech signals, you will also be given a set of transcripts for the database in a single file and two dictionaries, one in which legitimate words in the language are mapped sequences of sound units or sub-word unitsand another in which non-speech sounds are mapped to corresponding non-speech or speech-like sound units.

sphinx4 tutorial

We will refer to the former as the language dictionary and the latter as the filler dictionary. The decoder also consists of a set of programs, which have been compiled to give a single executable that will perform the recognition task, given the right inputs. The inputs that need to be given are: the trained acoustic models, a model index file, a language model, a language dictionary, a filler dictionary, and the set of acoustic signals that need to be recognized.

The data to be recognized are commonly referred to as test data. In addition to these components, you will need the acoustic models that you have trained for recognition. You will have to provide these to the decoder. While you train the acoustic models, the trainer will generate appropriately named model-index files. A model-index file simply contains numerical identifiers for each state of each HMM, which are used by the trainer and the decoder to access the correct sets of parameters for those HMM states.

With any given set of acoustic models, the corresponding model-index file must be used for decoding.This tutorial uses the sphinx4 API from the 5 pre-alpha release. The API described here is not supported in earlier versions. Sphinx4 is a pure Java speech recognition library. It can be used on servers and in desktop applications.

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Besides speech recognition, Sphinx4 helps to identify speakers, to adapt models, to align existing transcription to audio for timestamping and more. As any library in Java all you need to do to use sphinx4 is to add the jars to the dependencies of your project and then you can write code using the API.

The easiest way to use sphinx4 is to use modern build tools like Apache Maven or Gradle. Sphinx-4 is available as a maven package in the Sonatype OSS repository. In gradle you need the following lines in build. To use sphinx4 in your maven project specify this repository in your pom. Then add sphinx4-core to the project dependencies:.

Add sphinx4-data to the dependencies as well if you want to use the default US English acoustic and language models:.

In that case you can just include sphinx4 libraries into your project with the help of your IDE. You can also use Sphinx4 in a non-maven project. In this case you need to download the jars from the repository manually. You might also need to download the dependencies which we try to keep small and include them in your project. You need the sphinx4-core jar and the sphinx4-data jar if you are going to use US English acoustic model:. To quickly start with sphinx4, create a java project as described above, add the required dependencies and type the following simple code:.

This simple code snippet transcribes the file test. For most of the speech recognition jobs high-level interfaces should be sufficient. Basically, you will only have to setup four attributes:. The first three attributes are set up using a Configuration object which is then passed to a recognizer.

Building a language model

The way to connect to a speech source depends on your concrete recognizer and usually is passed as a method parameter. A Configuration is used to supply the required and optional attributes to the recognizer. The LiveSpeechRecognizer uses a microphone as the speech source. You can pass the data from a file, a network socket or from an existing byte array. The decoder does not support other formats.

If the audio format does not match, you will not get any results. This means, you need to convert your audio to a proper format before decoding. A SpeechAligner time-aligns text with audio speech. A SpeechResult provides access to various parts of the recognition result, such as the recognized utterance, a list of words with timestamps, the recognition lattice, etc.

A number of sample demos are included in the sphinx4 sources in order to give you an understanding how to run sphinx4. You can run them from the sphinx4-samples jar:. If you are going to start with a demo please do not modify the demo inside the sphinx4 sources. Instead, copy the code into your project and modify it there.Invocation of sphinx-quickstart. Install Sphinx, either from a distribution package or from PyPI with. The root directory of a Sphinx collection of reStructuredText document sources is called the source directory.

This directory also contains the Sphinx configuration file conf. Sphinx comes with a script called sphinx-quickstart that sets up a source directory and creates a default conf. Just run.

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It created a source directory with conf. This is one of the main things that Sphinx adds to reStructuredText, a way to connect multiple files to a single hierarchy of documents.

Directives can have arguments, options and content. Each directive decides whether it can have arguments, and how many.

The maxdepth is such an option for the toctree directive. Content follows the options or arguments after a blank line. Each directive decides whether to allow content, and what to do with it.

A common gotcha with directives is that the first line of the content must be indented to the same level as the options are. This is exactly how the toctree for this documentation looks. The documents to include are given as document name s, which in short means that you leave off the file name extension and use slashes as directory separators.

Read more about the toctree directive. Also, Sphinx now knows about the order and hierarchy of your documents. They may contain toctree directives themselves, which means you can create deeply nested hierarchies if necessary. In Sphinx source files, you can use most features of standard reStructuredText. There are also several features added by Sphinx. For example, you can add cross-file references in a portable way which works for all output types using the ref role.

A build is started with the sphinx-build program, called like this:.

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See Invocation of sphinx-quickstart for all options that sphinx-build supports. However, sphinx-quickstart script creates a Makefile and a make. Execute make without an argument to see which targets are available.I have seen and crawled the web for 6, 7 hours trying to find a simple tutorial that shows how to transcribe wav files. Tutorial describes new updated API for sphinx4. You can checkout corresponding code from the branch:.

I like this new interface, however it seems to have has some bugs in it. The whole input file is recognized as one utterance instead of breaking it up in multiple utterances. I am not done yet to figure out problem 2, the missing time stamps, what I have found so far is that the Token. I am posting my findings so far because if someone can fix this faster than I can I would be more than happy to update from svn.

Otherwise I'll report back here when I find more Overall, latticedemo xml config is way more reasonable than current hl-interface common config and the latter must be replaced with the former. As for times, keepAllTokens property in search manager must be set to true, that should solve the time issue temporary. The proper fix will require rework of the token itself which should keep time reference, I wanted to do that for a long time but this change is still pending.

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Resources Blog Articles Deals. Menu Help Create Join Login. A beginner's tutorial. Forum: Sphinx4 Help. Creator: Jhon. Created: Updated: GitHub is home to over 40 million developers working together to host and review code, manage projects, and build software together. If nothing happens, download GitHub Desktop and try again. If nothing happens, download Xcode and try again.

If nothing happens, download the GitHub extension for Visual Studio and try again. Skip to content. Dismiss Join GitHub today GitHub is home to over 40 million developers working together to host and review code, manage projects, and build software together.

Sign up. Java Branch: master. Find file. Sign in Sign up. Go back. Launching Xcode If nothing happens, download Xcode and try again. Latest commit. Latest commit 32df Nov 24, Sphinx-4 Speech Recognition System Sphinx-4 is a state-of-the-art, speaker-independent, continuous speech recognition system written entirely in the Java programming language.

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The design of Sphinx-4 is based on patterns that have emerged from the design of past systems as well as new requirements based on areas that researchers currently want to explore.

To exercise this framework, and to provide researchers with a "research-ready" system, Sphinx-4 also includes several implementations of both simple and state-of-the-art techniques. The framework and the implementations are all freely available via open source under a very generous BSD-style license. Because it is written entirely in the Java programming language, Sphinx-4 can run on a variety of platforms without requiring any special compilation or changes.

sphinx4 tutorial

We've tested Sphinx-4 on the following platforms with success. Sincerely, The Sphinx-4 Team: in alph. You signed in with another tab or window. Reload to refresh your session. You signed out in another tab or window. Update docs somewhat. Jan 30, Nov 23, Updated the en-us dict. May 2, Allphone does not return lattices.

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Jul 26, Allow relative path too. Apr 5, See for details. Mar 25,


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