Open Source Speech Software
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Speech Software
View 4317 business solutionsBrowse 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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Our robust pre-built connectors and our no-code, drag-and-drop interface makes it easy and fast to automatically sync vendors, invoices, and invoice payment data between Tipalti and your ERP or accounting software.
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We design our technology to make workforce management easier. APS offers core HR, payroll, benefits administration, attendance, recruiting, employee onboarding, and more.
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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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eGuideDog project develops free software for the blind. Currently, we focus on WebSpeech, Ekho TTS and WebAnywhere.
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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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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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Define and Deliver Comprehensive Cybersecurity Services. Security threats continue to grow, and your clients are most likely at risk. Small- to medium-sized businesses (SMBs) are targeted by 64% of all cyberattacks, and 62% of them admit lacking in-house expertise to deal with security issues. Now technology solution providers (TSPs) are a prime target. Enter ConnectWise Cybersecurity Management (formerly ConnectWise Fortify) — the advanced cybersecurity solution you need to deliver the managed detection and response protection your clients require. Whether you’re talking to prospects or clients, we provide you with the right insights and data to support your cybersecurity conversation. From client-facing reports to technical guidance, we reduce the noise by guiding you through what’s really needed to demonstrate the value of enhanced strategy.
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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. -
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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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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. -
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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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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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A Freelancer Management System (FMS) is a platform that enables companies to organize, track projects and manage payments with their freelance and contract workforce. TalentDesk.io does what a freelance management platform or FMS does and more. Driving the convergence of your contract, freelance and full-time employees, it ensures all resources are managed efficiently.
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Open JTalk is a Japanese text-to-speech synthesis system. This software is released under the Modified BSD license.
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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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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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Coqui STT
The deep learning toolkit for speech-to-text
Coqui STT is a fast, open-source, multi-platform, deep-learning toolkit for training and deploying speech-to-text models. Coqui STT is battle-tested in both production and research. Multiple possible transcripts, each with an associated confidence score. Experience the immediacy of script-to-performance. With Coqui text-to-speech, production times go from months to minutes. With Coqui, the post is a pleasure. Effortlessly clone the voices of your talent and have the clone handle the problems in post. With Coqui, dubbing is a delight. Effortlessly clone the voice of your talent into another language and let the clone do the dub. With text-to-speech, experience the immediacy of script-to-performance. Cast from a wide selection of high-quality, directable, emotive voices or clone a voice to suit your needs. With Coqui text-to-speech, production times go from months to minutes. -
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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. -
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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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annyang!
Speech recognition for your site
annyang is a tiny javascript library that lets your visitors control your site with voice commands. annyang supports multiple languages, has no dependencies, weighs just 2kb and is free to use. annyang understands commands with named variables, splats, and optional words. Use named variables for one word arguments in your command. Use splats to capture multi-word text at the end of your command (greedy). Use optional words or phrases to define a part of the command as optional. annyang plays nicely with all browsers, progressively enhancing browsers that support SpeechRecognition, while leaving users with older browsers unaffected. Grab the latest version of annyang.min.js, drop it in your html, and start adding commands. You can easily add a GUI for the user to interact with Speech Recognition using Speech KITT. Speech KITT is fully customizable and comes with many different themes, and instructions on how to create your own designs. -
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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
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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.
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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.
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Omilo - a text to speech application
Omilo is a simple text to speech application
Omilo is a simple text to speech application for Windows and Linux using Festival, Flite, Marytts and Piper voices. -
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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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RHVoice
Free open source speech synthesizer for Russian and other languages
RHVoice is a free and open-source multilingual speech synthesizer. Its developers hope to give more visually impaired people the ability to use a good free synthesis voice reading in their native language with their screen reader. We are especially interested in supporting those languages for which there are currently no good voices that could be used with a screen reader. The creator of RHVoice, Olga Yakovleva, is blind herself. Many of the contributors to the RHVoice project, both programmers and non-programmers, are blind or partially sighted. -
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XZVoice
Free and open source text-to-speech software
Text-to-speech software developed by Electron + vue + ElementUI + js. The high-fidelity and flexible configuration of speech synthesis products opens up the closed loop of human-computer interaction and enables applications to sound realistically. A variety of timbres are available, and functions such as adjusting speech rate, intonation, and volume are provided. Technically, multi-level rhythmic pauses are taken into account to achieve the purpose of natural synthesizing rhythm, and comprehensively use acoustic parameters and linguistic parameters to establish multiple automatic prediction models based on deep learning. Using massive audio data to train the pronunciation model, the synthetic sound is real, full, cadenced, and expressive, and the MOS score has reached the professional level in the industry. -
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Voice keyboard/dictation. Aims to be a total substitute for a keyboard. Spell out words letter by letter (using code: alpha, bravo, ..). Arrow keys, modifiers work. Speak whole words (but whole word accuracy is not good). Attach commands to some word
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.