Speech Clear Filters

Browse free open source Speech software and projects below. Use the toggles on the left to filter open source Speech software by OS, license, language, programming language, and project status.

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  • 1
    eSpeak: speech synthesis
    Text to Speech engine for English and many other languages. Compact size with clear but artificial pronunciation. Available as a command-line program with many options, a shared library for Linux, and a Windows SAPI5 version.
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    Downloads: 2,306 This Week
    Last Update:
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  • 2
    DeepSpeech

    DeepSpeech

    Open source embedded speech-to-text engine

    DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers. DeepSpeech is an open-source Speech-To-Text engine, using a model trained by machine learning techniques based on Baidu's Deep Speech research paper. Project DeepSpeech uses Google's TensorFlow to make the implementation easier. A pre-trained English model is available for use and can be downloaded following the instructions in the usage docs. If you want to use the pre-trained English model for performing speech-to-text, you can download it (along with other important inference material) from the DeepSpeech releases page.
    Downloads: 43 This Week
    Last Update:
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  • 3
    SpeechRecognition

    SpeechRecognition

    Speech recognition module for Python

    Library for performing speech recognition, with support for several engines and APIs, online and offline. Recognize speech input from the microphone, transcribe an audio file, save audio data to an audio file. Show extended recognition results, calibrate the recognizer energy threshold for ambient noise levels (see recognizer_instance.energy_threshold for details). Listening to a microphone in the background, various other useful recognizer features. The easiest way to install this is using pip install SpeechRecognition. The first software requirement is Python 2.6, 2.7, or Python 3.3+. This is required to use the library. PyAudio is required if and only if you want to use microphone input (Microphone). PyAudio version 0.2.11+ is required, as earlier versions have known memory management bugs when recording from microphones in certain situations. To hack on this library, first make sure you have all the requirements listed in the "Requirements" section.
    Downloads: 24 This Week
    Last Update:
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  • 4
    NoiseGator (Noise Gate)

    NoiseGator (Noise Gate)

    A simple noise gate app intended for use with VOIPs like Skype.

    Ever wanted to cut out background noise when talking with others on Skype? Now it's possible! NoiseGator is a light-weight noise gate application that routes audio through an audio input to an audio output. In real-time the audio level is analysed and if the average level is higher than the threshold the audio bypasses as normal. However, if the average level goes below the threshold, the gate closes and the audio is cut. When used with a virtual audio cable it can act as a noise gate for a either a sound input(microphone) or sound output(speakers). Can also be used to gate noise from your own mic or play your microphone through your speakers. REQUIREMENTS: - Java 7 or higher for Windows. - Java 6 or higher for Mac. Java 7 recommended. - A virtual audio cable is required for use with VOIPs: For Windows users I recommend the VB-Cable driver (http://vb-audio.pagesperso-orange.fr/Cable/index.htm). Mac users can use SoundFlower.
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    Downloads: 750 This Week
    Last Update:
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  • Manage Properties Better For Free Icon
    Manage Properties Better For Free

    For small to mid-sized landlords and property managers

    Innago is a free and easy-to-use property management solution. Whether you have 1 unit or 1000, student housing, or commercial properties, Innago is built for you. Our software is designed to save you time and money, so you can spend more time doing the things that matter most.
  • 5
    MARF is a general cross-platform framework with a collection of algorithms for audio (voice, speech, and sound) and natural language text analysis and recognition along with sample applications (identification, NLP, etc.) of its use, implemented in Java.
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    Downloads: 354 This Week
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  • 6
    eGuideDog free software for the blind
    eGuideDog project develops free software for the blind. Currently, we focus on WebSpeech, Ekho TTS and WebAnywhere.
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    Downloads: 190 This Week
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  • 7
    Mumble

    Mumble

    Low-latency, high quality voice chat for gamers

    Mumble is an open source, low-latency, high quality voice chat software primarily intended for use while gaming. It includes game linking, so voice from other players comes from the direction of their characters, and has echo cancellation so the sound from your loudspeakers won't be audible to other players.
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    Downloads: 159 This Week
    Last Update:
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  • 8
    WaveSurfer
    WaveSurfer is an open source tool for sound visualization and manipulation. Typical applications are speech/sound analysis and sound annotation/transcription. WaveSurfer may be extended by plug-ins as well as embedded in other applications.
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    Downloads: 139 This Week
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  • 9
    Open JTalk is a Japanese text-to-speech synthesis system. This software is released under the Modified BSD license.
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    Downloads: 614 This Week
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  • 10
    Simple TTS Reader
    Simple TTS Reader is a small clipboard reader. Simply copy any text, and it will be read aloud. You can choose any installed speech engine, e.g. Microsoft Anna. This text-to-speech utility can also be minimized to tray. Requires .NET Framework 2.0.
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    Downloads: 106 This Week
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  • 11
    TTS

    TTS

    Deep learning for text to speech

    TTS is a library for advanced Text-to-Speech generation. It's built on the latest research, was designed to achieve the best trade-off among ease-of-training, speed, and quality. TTS comes with pre-trained models, tools for measuring dataset quality, and is already used in 20+ languages for products and research projects. Released models in PyTorch, Tensorflow and TFLite. Tools to curate Text2Speech datasets underdataset_analysis. Demo server for model testing. Notebooks for extensive model benchmarking. Modular (but not too much) code base enabling easy testing for new ideas. Text2Spec models (Tacotron, Tacotron2, Glow-TTS, SpeedySpeech). Speaker Encoder to compute speaker embeddings efficiently. Vocoder models (MelGAN, Multiband-MelGAN, GAN-TTS, ParallelWaveGAN, WaveGrad, WaveRNN). If you are only interested in synthesizing speech with the released TTS models, installing from PyPI is the easiest option.
    Downloads: 3 This Week
    Last Update:
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  • 12
    FreeTTS is a speech synthesis engine written entirely in the Java(tm) programming language. FreeTTS was written by the Sun Microsystems Laboratories Speech Team and is based on CMU's Flite engine. FreeTTS also includes a partial JSAPI 1.0
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    Downloads: 219 This Week
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  • 13
    MMDAgent is the toolkit for building voice interaction systems. Users can design users own dialog scenario, 3D agents, and voices. This software is released under the Modified BSD license.
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    Downloads: 93 This Week
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  • 14
    SPTK is a suite of speech signal processing tools for UNIX environments, e.g., LPC analysis, PARCOR analysis, LSP analysis, PARCOR synthesis filter, LSP synthesis filter, vector quantization techniques, and other extended versions of them.
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    Downloads: 48 This Week
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  • 15
    hts_engine is software to synthesize speech waveform from HMMs trained by the HMM-based speech synthesis system (HTS). This software is released under the Modified BSD license.
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    Downloads: 230 This Week
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  • 16
    a tool for segmenting, labeling and transcribing speech
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    Downloads: 97 This Week
    Last Update:
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  • 17
    Wrapper for vendors to simplify usage of the Java Speech API (JSR 113). Note that the spec is an untested early access and that there may be changes in the API.
    Downloads: 23 This Week
    Last Update:
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  • 18
    srt-translator

    srt-translator

    Subtitle translator from one natural language to other.

    Translating subtitles in format SubRip from one natural language to other. It is based on Google Translate without API and therefore without payment. Translator have automatic and manual spell checkers.
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    Downloads: 57 This Week
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  • 19
    TranscriberAG is designed for assisting the manual annotation of speech signals. It provides a user-friendly GUI for segmenting long duration speech recordings, transcribing them, labeling speech turns, topic changes and acoustic conditions.
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    Downloads: 31 This Week
    Last Update:
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  • 20
    Virtual Hypnotist is a software application that aims to provide a virtual interactive hypnosis session framework, for many uses. It is a rewrite of the Hypnotizer 2000 software. See the readme.txt file for legal info.
    Downloads: 24 This Week
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  • 21
    DonnerLaParole
    Clavier virtuel et synthétiseur vocal pour les personnes ne pouvant plus parler et ayant du mal à utiliser leurs mains. Virtual keyboard and speech synthetiser for people with reduced mobility and unability to speak. In French and english.
    Downloads: 8 This Week
    Last Update:
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  • 22
    Epos TTS System

    Epos TTS System

    Epos is a language independent rule-driven Text-to-Speech (TTS) system

    Epos is a language independent rule-driven Text-to-Speech (TTS) system primarily designed to serve as a research tool. Epos is (or tries to be) independent of the language processed, linguistic description method, and computing environment.
    Downloads: 19 This Week
    Last Update:
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  • 23
    A Biblia Falada é um software para leitura e estudo da Biblia Sagrada. Muito simples de usar e totalmente acessível para deficientes visuais, traz, além do novo sistema de leitura, os textos completos da edição Revista e Atualizada.
    Downloads: 8 This Week
    Last Update:
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  • 24
    A language teaching program and library based on C. It includes sound snippets featuring native speakers. You can create, edit and use various lessons and learn via an optional GTK2 interface.
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    Downloads: 26 This Week
    Last Update:
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  • 25
    The project provides a ready-to-use interface for the julius CSR engine for a handicapped child which is not able to use the keyboard well. It integrates into X11 and Windows. Find out how you can help: http://simon-listens.org/index.php?support
    Downloads: 4 This Week
    Last Update:
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Guide to Open Source Speech Software

Open source speech software is a type of technology that allows users to use computers to understand, recognize and generate human speech. It utilizes Natural Language Processing (NLP) in order to interpret spoken language and convert it into text or commands. Open source speech software is based on publicly-available algorithms and code, which can be modified and distributed freely by anyone who has access to the code.

Open source speech software provides a platform for developers to build applications that interact with humans through natural language dialogue. This type of software enables more efficient communication between people, machines and other devices; allowing for speedier interactions at low cost. In addition, open source solutions allow changes and improvements to happen more quickly as the community can iterate on ideas faster than closed-source solutions. As such, open source speech solutions are often better suited for rapidly changing environments like businesses or industry segments that need quick responses from their voice recognition tools.

One of the most popular open source libraries for building voice assistant applications is Rasa NLU (Natural Language Understanding). Rasa NLU processes user input given in natural language form, such as text or voice, into structured data so that the conversation system can use the information provided by its users appropriately. Rasa NLU has been used successfully in many projects ranging from customer service bots to healthcare assistants or vehicle interfaces. Other popular open source libraries include CMUSphinx Speech Recognition Toolkit, Mozilla DeepSpeech, Google Speech API and Kaldi Speech Recognition Toolkit among others.

These platforms have opened up tremendous opportunities for developers looking to create innovative solutions utilizing machine learning capabilities like automatic speech recognition (ASR), natural language understanding (NLU) and Automatic Speech Synthesis (Text-to-Speech) allowing those with limited resources easier access to these technologies. With advancements being made regularly in this field there are now more powerful tools available than ever before making it easier than ever before build sophisticated conversational AI products. So if you’re looking at creating an application leveraging voice as its primary interface, then considering an open source alternative could help you realize your vision faster while being save costs at the same time.

Open Source Speech Software Features

  • Automatic Speech Recognition (ASR): Automatic Speech Recognition is a feature that allows the computer to recognize spoken language and convert it into text. It supports multiple languages, making it easier for users to communicate in their native language.
  • Text-to-Speech (TTS): Text-to-Speech is a feature that can read out loud written text, with advanced settings allowing users to customize voices and characters used in their speech output. This feature helps those with literacy difficulties or visual impairments access information more quickly and easily.
  • Natural Language Processing (NLP): NLP provides the ability to interpret natural language by recognizing syntactic and semantic relationships between words. This enables accurate responses when questions are posed in different ways, as well as understanding context better than other AI systems can achieve.
  • Voice Commands: Voice commands allow the user to issue commands or control the system without having to use a keyboard or mouse, providing an accessible solution for both people with disabilities and those who prefer hands-free operation of their device.
  • Voice Activation: Voice activation is similar to voice commands but goes one step further by using wake words such as "Hey Siri" or "Ok Google" in order for the system to respond more accurately whilst also helping prevent accidental activation when not desired.
  • Speech Analytics: Speech analytics analyses voice recordings to extract insights and patterns that can be used to optimize customer service, security features, or marketing. This is of particular benefit for businesses as it helps them better understand their customers and build relationships with them on a deeper level.
  • Text-to-Sign Language (TTSL): For those who are hard of hearing or deaf, Text-to-Sign Language converts written text into a sign language video representation. This ensures that information is accessible for all individuals, regardless of their hearing status.

What Types of Open Source Speech Software Are There?

  • Text to Speech Software: Text to speech software reads out written text, either in real-time or as a pre-recorded audio file. It can be used to create audio books, podcasts, automated phone systems, and other voice-based applications.
  • Voice Recognition Software: Voice recognition software converts spoken language into digital data that can be understood by computers. It is often used for dictation, automated call routing and customer service applications.
  • Natural Language Processing: Natural language processing (NLP) is a branch of artificial intelligence that enables machines to understand verbal commands and interpret human language. NLP technology can recognize words, phrases and sentences in natural conversations and use this information to generate responses tailored specifically for each user.
  • Speech Synthesis Software: Speech synthesis software creates synthetic voices from text inputted by the user. This technology is often used for multi-lingual translations, virtual assistants and voice actors in video games or animations.
  • Speech Analytics Software: Speech analytics software interprets vocal interactions between people in order to provide insights into customer sentiment or employee performance. This type of software uses machine learning algorithms to analyze recordings of conversations or calls and provide useful data about the topics discussed during those interactions.

Benefits of Open Source Speech Software

  • Increased Customization: Open source speech software provides users with the ability to customize their speech recognition experience according to their own needs and preferences. This allows developers to tailor their software to widely different applications, making it better suited for certain tasks than commercial solutions.
  • Improved Security: When developing open source speech software, developers are able to ensure that all security issues have been addressed before releasing it into the wild. This makes open source solutions much more secure than closed source alternatives when dealing with sensitive data.
  • Reduced Costs: One of the major benefits associated with open source speech software is its cost-effectiveness. Using open source solutions can significantly reduce the overall costs of development, as you do not need to purchase expensive licenses for proprietary software components or use costly cloud services for your application.
  • Faster Production Times: With access to a wide range of libraries and code snippets from multiple sources, developers using open source software are able to quickly develop new features and functions without having to spend time writing them from scratch. This can result in faster production times, allowing projects to be completed sooner and more efficiently than if they were produced using closed source alternatives.
  • Stronger Support Network: The number of people contributing towards an open source project can create a strong support network for users who may be struggling with specific issues or require additional help or advice when carrying out certain tasks. This is especially beneficial when working on complex projects where assistance may be required at any given moment.
  • Enhanced Collaboration: Open source speech software can allow teams of developers to work together more effectively and efficiently, as everyone has access to the same tools and resources. This can reduce the amount of time required to discuss changes or additions to a project, allowing for greater collaboration between multiple parties and improved productivity in general.

Types of Users That Use Open Source Speech Software

  • Students: Students use open source speech software to improve their public speaking skills, create presentations and reports, and hone their verbal communication abilities.
  • Professionals: Professionals often use open source speech software to develop presentation materials for conferences and meetings, build webinar content, practice delivering speeches, and more.
  • Recreational Users: Recreational users may leverage open source speech software to become a better public speaker during events like weddings or other special occasions.
  • Non-profit Organizations: Non-profits often utilize open source speech software for virtual volunteers to record audio for podcasts or videos or on-line classes. It is also used to train staff members in presenting ideas at workshops and sharing stories from their organization with wider communities.
  • Media Professionals: Journalists and media professionals turn to open source speech software for recording interviews or narration pieces as well as creating training materials. They also appreciate the flexibility of the platform for live streaming of events such as panel discussions or performances online.
  • Health Care Providers: Doctors, nurses and other medical professionals are increasingly utilizing free speech recognition tools from open source platforms in order to streamline patient visits and process medical paperwork more efficiently while still providing quality care.
  • Business Owners: Open source speech software can be used to generate automated customer service responses, process orders, and develop virtual marketing strategies. They also enable entrepreneurs to record audio for their own podcasts or videos as well as create scripts for corporate events such as online conferences or webinars.
  • Educators: Schools, universities and other educational institutions make use of open source speech software in order to teach proper pronunciation and correct grammar usage. It is typically utilized by teachers when giving lectures or presenting materials online. It can also be used for virtual classrooms, allowing students from different countries to access content in real-time.
  • Governments: Government agencies leverage open source speech software to design meetings with the public, keep records of past sessions and plan future events. Additionally it is used by officials in training programs alongside cultural language classes.

How Much Does Open Source Speech Software Cost?

Open source speech software is typically available for free, though certain versions may require a fee. Depending on the type of software you need, you may be able to find open source alternatives that will provide ample functionality and advantages over paid solutions.

For example, some open source voice recognition tools such as CMU Sphinx are available for free. There are also many open source text-to-speech engines like Festival or eSpeak that can be used to generate audio from typed words. Additionally, some companies offer their own proprietary versions of open source speech software with additional features or customization options at no or low cost. For those who need higher quality results and willing to pay, there are also commercial speech products such as Microsoft Speech Platform SDK or Nuance Dragonspeak Professional that offer a range of features and functions beyond what’s included in most open source solutions.

Overall, the cost of using an open source solution can vary greatly depending on your specific needs and preferences. However, it’s safe to say that these types of tools often come at little or no cost which makes them attractive for users on a budget looking for reliable speech technology without breaking the bank.

What Software Does Open Source Speech Software Integrate With?

Integrating with open source speech software can involve many different types of software. For example, text-to-speech (TTS) programs are used to generate audible speech from text and can be easily integrated with open source software. Natural Language Processing (NLP) solutions are also often integrated with open source programs in order to interpret user input and provide meaningful output. Additionally, telephony systems such as VoIP often use open source software for their backend infrastructure. This allows users to communicate via voice or video over an internet connection using the same system that powers the development of open source speech applications. Finally, transcription services that take audio files and produce written text can be integrated with open source tools to provide a more robust experience for users when interacting with this type of program.

Open Source Speech Software Trends

  • Increased Adoption: Open source speech software is becoming more widely adopted, with businesses and developers increasingly recognizing the benefits it offers. This is due to its flexibility, cost-effectiveness, and ability to customize applications according to specific needs.
  • Enhanced Functionality: Open source speech software continues to evolve and improve with each passing year, as developers add new features and capabilities. This includes better natural language processing (NLP) capabilities and improved accuracy in speech recognition.
  • Greater Automation: Open source speech software has enabled greater automation of tasks, allowing businesses to streamline their processes and reduce labor costs. This has been particularly beneficial for customer service operations where automated systems can now be used to quickly respond to customer inquiries.
  • Improved Accessibility: The development of open source speech software has made it easier for people with disabilities to access technology. For instance, speech recognition software can be used to assist those with visual impairments who may otherwise have difficulty using a computer or other device.
  • Increased Security: With open source speech software, businesses can be assured that their data is secure from hackers and other malicious actors. This is due to the fact that open source code can be scrutinized by the public for any potential vulnerabilities or bugs before being deployed in production environments.
  • Increased Support: The open source community has become increasingly supportive, with many developers now offering support and guidance to users. This makes it easier for businesses to take advantage of open source software without having to worry about potential technical issues.

How Users Can Get Started With Open Source Speech Software

Getting started with using open source speech software can be done in a few simple steps. First, the user should do research to find out which speech software best suits their needs. The user should also determine whether they want to use an open source program or purchase one from a vendor. Once they have identified the right program for them, they should download it and install it on their computer.

Next, the user will need to familiarize themselves with the software’s features and functions, as well as any tutorials or documentation that come with it. They should also look for additional resources online that provide information about how to use the particular program effectively. Additionally, depending on the type of speech software chosen, users may need to set up custom parameters depending on their individual preferences and needs.

Following setup of any necessary parameters, users can begin exploring various aspects of the software in order to better understand how it works and what capabilities it provides. This includes experimenting with text-to-speech (TTS) input data and testing other features such as voice recognition accuracy or customization options available for outputting audio files into different formats for playback or further processing. It’s always a good idea to save multiple sample recordings so you can compare your results across sessions and track improvements over time.

Finally, once users feel confident enough in using the software they can start putting all these pieces together into more complex tasks such as developing applications incorporating TTS technology or building conversational agents powered by natural language processing (NLP). Open source speech platforms offer unique opportunities for creative expression through sound engineering so don't be afraid to get creative.