Select any text and click on the icon to listen!
ByGSpeech
G

Demos

Full Page Player Demo - SoundCloud Style

Button Player Demo

Circle Player Demo

Note: Use the dots icon to open options panel. Use the Globe icon to change audio language, Users icon to choose voice.
You can set one of 16 beautiful themes or create your own, adjust sizes and much more.

Full Page Player - New York Style

Full Page Player - Minimal Style

You can see GSpeech different examples on this page. Full player with multiple languages and voices, RHT player, welcome messages and much more.

Multiple languages supported

GSpeech supports the following languages:

  • Afrikaans
  • Albanian
  • Arabic
  • Armenian
  • Belarusian
  • Basque
  • Bengali
  • Bosnian
  • Bulgarian
  • Catalan
  • Chinese (Simplified)
  • Chinese (Traditional)
  • Croatian
  • Czech
  • Danish
  • Dutch
  • English (Australia)
  • English (UK)
  • English (India)
  • English (United States)
  • Estonian
  • Filipino
  • Finnish
  • French (Canada)
  • French (France)
  • Galician
  • German
  • Greek
  • Gujarati
  • Hebrew
  • Hindi
  • Hungarian
  • Icelandic
  • Indonesian
  • Italian
  • Japanese
  • Javanese
  • Kannada
  • Kazakh
  • Khmer
  • Korean
  • Latin
  • Latvian
  • Lithuanian
  • Macedonian
  • Malay
  • Malayalam
  • Marathi
  • Maori
  • Myanmar
  • Nepali
  • Norwegian
  • Persian
  • Polish
  • Portuguese (Brazil)
  • Portuguese (Portugal)
  • Punjabi (Gurmukhi)
  • Punjabi (Shahmukhi)
  • Romanian
  • Russian
  • Serbian
  • Sinhala
  • Slovak
  • Slovenian
  • Spanish (Spain)
  • Spanish (United States)
  • Sundanese (Indonesia)
  • Swahili
  • Swedish
  • Tamil
  • Telugu
  • Thai
  • Turkish
  • Ukrainian
  • Urdu
  • Vietnamese
  • Yue Chinese
  • Welsh

Try English

Try Spanish

Try French

Try German

Try Italian

Try Russian

Try Japanese

Try Chinese

Different 80+ Themes which will match with any website design!

Move your content to next level! Try GSpeech now!
Sign Up Free
Text-to-speech technology can create more engaging content for customers. Convert your articles, blog or any content into high-quality text-to-speech audio for users who prefer listening over reading. It also shows that you’re willing to go the extra mile to accommodate your customers. Transforming text into speech can provide an engaging experience for audiences, encouraging return visits! Text to Speech by GSpeech service gives apportunity to add accessibility feature in any site in just one click. Text to Speech by GSpeech service implements Web Content Accessibility Guidelines (WCAG) in the site.
La tecnología de conversión de texto a voz puede crear contenido más atractivo para los clientes. Convierta sus artículos, blogs o cualquier contenido en audio de conversión de texto a voz de alta calidad para los usuarios que prefieren escuchar en lugar de leer. También demuestra que está dispuesto a hacer un esfuerzo adicional para satisfacer a sus clientes. La transformación de texto a voz puede proporcionar una experiencia atractiva para las audiencias, lo que fomenta las visitas recurrentes. El servicio de conversión de texto a voz de GSpeech brinda la oportunidad de agregar funciones de accesibilidad en cualquier sitio con solo un clic. El servicio de conversión de texto a voz de GSpeech implementa las Pautas de Accesibilidad al Contenido Web (WCAG) en el sitio.
La technologie de synthèse vocale peut créer un contenu plus attrayant pour les clients. Convertissez vos articles, votre blog ou tout autre contenu en audio de synthèse vocale de haute qualité pour les utilisateurs qui préfèrent écouter plutôt que lire. Cela montre également que vous êtes prêt à faire un effort supplémentaire pour satisfaire vos clients. La transformation du texte en parole peut offrir une expérience attrayante au public, encourageant les visites récurrentes ! Le service Text to Speech de GSpeech offre la possibilité d'ajouter une fonctionnalité d'accessibilité à n'importe quel site en un seul clic. Le service Text to Speech de GSpeech implémente les directives d'accessibilité du contenu Web (WCAG) sur le site.
Mit Text-to-Speech-Technologie können Sie ansprechendere Inhalte für Kunden erstellen. Wandeln Sie Ihre Artikel, Blogs oder andere Inhalte in hochwertige Text-to-Speech-Audiodateien für Benutzer um, die lieber zuhören als lesen. Es zeigt auch, dass Sie bereit sind, noch mehr zu tun, um Ihren Kunden entgegenzukommen. Die Umwandlung von Text in Sprache kann ein ansprechendes Erlebnis für das Publikum bieten und zu erneuten Besuchen anregen! Der Text-to-Speech-Dienst von GSpeech bietet die Möglichkeit, mit nur einem Klick eine Barrierefreiheitsfunktion in jede Site einzufügen. Der Text-to-Speech-Dienst von GSpeech implementiert die Web Content Accessibility Guidelines (WCAG) in die Site.
La tecnologia text-to-speech può creare contenuti più coinvolgenti per i clienti. Converti i tuoi articoli, blog o qualsiasi contenuto in audio text-to-speech di alta qualità per gli utenti che preferiscono ascoltare anziché leggere. Dimostra anche che sei disposto a fare uno sforzo in più per soddisfare i tuoi clienti. Trasformare il testo in parlato può offrire un'esperienza coinvolgente per il pubblico, incoraggiando le visite di ritorno! Il servizio Text to Speech di GSpeech offre l'opportunità di aggiungere funzionalità di accessibilità in qualsiasi sito con un solo clic. Il servizio Text to Speech di GSpeech implementa le Linee guida per l'accessibilità dei contenuti Web (WCAG) nel sito.
A tecnologia de conversão de texto em fala pode criar conteúdo mais envolvente para os clientes. Converta seus artigos, blog ou qualquer conteúdo em áudio de conversão de texto em fala de alta qualidade para usuários que preferem ouvir em vez de ler. Isso também mostra que você está disposto a ir além para acomodar seus clientes. Transformar texto em fala pode fornecer uma experiência envolvente para o público, incentivando visitas de retorno! O serviço Text to Speech by GSpeech oferece a oportunidade de adicionar recursos de acessibilidade em qualquer site com apenas um clique. O serviço Text to Speech by GSpeech implementa as Diretrizes de Acessibilidade de Conteúdo da Web (WCAG) no site.
Технология преобразования текста в речь может создавать более привлекательный контент для клиентов. Преобразуйте свои статьи, блог или любой контент в высококачественный текст в речь для пользователей, которые предпочитают слушать, а не читать. Это также показывает, что вы готовы пройти лишнюю милю, чтобы удовлетворить своих клиентов. Преобразование текста в речь может обеспечить увлекательный опыт для аудитории, поощряя повторные посещения! Служба преобразования текста в речь от GSpeech дает возможность добавить функцию доступности на любой сайт всего за один клик. Служба преобразования текста в речь от GSpeech реализует Руководство по обеспечению доступности веб-контента (WCAG) на сайте.
テキスト読み上げ技術により、顧客にとってより魅力的なコンテンツを作成できます。記事、ブログ、その他のコンテンツを高品質のテキスト読み上げオーディオに変換して、読むよりも聞くことを好むユーザーに対応します。また、顧客に対応するためにさらに努力する意思があることも示します。テキストを音声に変換すると、視聴者に魅力的な体験を提供でき、再訪問を促すことができます。GSpeech のテキスト読み上げサービスでは、ワンクリックで任意のサイトにアクセシビリティ機能を追加できます。GSpeech のテキスト読み上げサービスは、サイトに Web コンテンツ アクセシビリティ ガイドライン (WCAG) を実装します。
文本转语音技术可以为客户创建更具吸引力的内容。将您的文章、博客或任何内容转换为高质量的文本转语音音频，供喜欢聆听而非阅读的用户使用。这也表明您愿意付出更多努力来满足客户的需求。将文本转换为语音可以为观众提供引人入胜的体验，鼓励回访！GSpeech 的文本转语音服务让您只需单击一下即可在任何站点中添加无障碍功能。GSpeech 的文本转语音服务在站点中实施了 Web 内容无障碍指南 (WCAG)。
© 2012 - 2025 Creative Solutions. All Rights Reserved.
en en
you can see gspeech different examples on this page. full player with multiple languages and voices, rht player, welcome messages and much more.
Close context player
allowing people to converse with machines is a long-standing dream of human-computer interaction. the ability of computers to understand natural speech has been revolutionised in the last few years by the application of deep neural networks (e.g., google voice search). however, generating speech with computers — a process usually referred to as speech synthesis or text-to-speech (tts) — is still largely based on so-called concatenative tts, where a very large database of short speech fragments are recorded from a single speaker and then recombined to form complete utterances. this makes it difficult to modify the voice (for example switching to a different speaker, or altering the emphasis or emotion of their speech) without recording a whole new database. this has led to a great demand for parametric tts, where all the information required to generate the data is stored in the parameters of the model, and the contents and characteristics of the speech can be controlled via the inputs to the model. so far, however, parametric tts has tended to sound less natural than concatenative. existing parametric models typically generate audio signals by passing their outputs through signal processing algorithms known as vocoders. wavenet changes this paradigm by directly modeling the raw waveform of the audio signal, one sample at a time. as well as yielding more natural-sounding speech, using raw waveforms means that wavenet can model any kind of audio, including music.
Close context player
add voice to your website, grow your subscribers by creating audio version of your content, which nowadays is a very popular trend. enable text-to-speech technology on your site to read content out loud for your audience. with gspeech your audience can finally listen in to your content while being busy working, commuting, exercising, and having their eyes and hands full. with gspeech you can increase user engagement and time spent on your site by allowing your visitors to listen in to the content of your website in the background while they’re working, commuting, eating, or having their hands busy.
Close context player
you can improve your website’s accessibility which is often times forgotten and to empower visitors who have visual impairment and reading disabilities to still completely consume your content without the complications of reading. lastly, you can grow your subscribers and cast a wider net of audience who are more into listening to podcasts and audiobooks which nowadays is a very popular trend and growing behavior of people to consume content. are you ready to add voice to your website? try gspeech now!
Close context player
you can improve your website’s accessibility which is often times forgotten and to empower visitors who have visual impairment and reading disabilities to still completely consume your content without the complications of reading. lastly, you can grow your subscribers and cast a wider net of audience who are more into listening to podcasts and audiobooks which nowadays is a very popular trend and growing behavior of people to consume content. are you ready to add voice to your website? try gspeech now!
Close context player
why do we use lorem ipsum? it is a long established fact that a reader will be distracted by the readable content of a page when looking at its layout. the point of using lorem ipsum is that it has a more-or-less normal distribution of letters, as opposed to using simon you are great, making it look like readable english. many desktop publishing packages and web page editors now use lorem ipsum as their default model text, and a search for 'lorem ipsum' will uncover many web sites still in their infancy. various versions have evolved over the years, sometimes by accident, sometimes on purpose (injected humour and the like).
Close context player
text-to-speech technology can create more engaging content for customers. convert your articles, blog or any content into high-quality text-to-speech audio for users who prefer listening over reading. it also shows that you’re willing to go the extra mile to accommodate your customers. transforming text into speech can provide an engaging experience for audiences, encouraging return visits! text to speech by gspeech service gives apportunity to add accessibility feature in any site in just one click. text to speech by gspeech service implements web content accessibility guidelines (wcag) in the site.
Close context player
la tecnología de conversión de texto a voz puede crear contenido más atractivo para los clientes. convierta sus artículos, blogs o cualquier contenido en audio de conversión de texto a voz de alta calidad para los usuarios que prefieren escuchar en lugar de leer. también demuestra que está dispuesto a hacer un esfuerzo adicional para satisfacer a sus clientes. la transformación de texto a voz puede proporcionar una experiencia atractiva para las audiencias, lo que fomenta las visitas recurrentes. el servicio de conversión de texto a voz de gspeech brinda la oportunidad de agregar funciones de accesibilidad en cualquier sitio con solo un clic. el servicio de conversión de texto a voz de gspeech implementa las pautas de accesibilidad al contenido web (wcag) en el sitio.
Cerrar reproductor de contexto
la technologie de synthèse vocale peut créer un contenu plus attrayant pour les clients. convertissez vos articles, votre blog ou tout autre contenu en audio de synthèse vocale de haute qualité pour les utilisateurs qui préfèrent écouter plutôt que lire. cela montre également que vous êtes prêt à faire un effort supplémentaire pour satisfaire vos clients. la transformation du texte en parole peut offrir une expérience attrayante au public, encourageant les visites récurrentes! le service text to speech de gspeech offre la possibilité d'ajouter une fonctionnalité d'accessibilité à n'importe quel site en un seul clic. le service text to speech de gspeech implémente les directives d'accessibilité du contenu web (wcag) sur le site.
Fermer le lecteur de contexte
mit text-to-speech-technologie können sie ansprechendere inhalte für kunden erstellen. wandeln sie ihre artikel, blogs oder andere inhalte in hochwertige text-to-speech-audiodateien für benutzer um, die lieber zuhören als lesen. es zeigt auch, dass sie bereit sind, noch mehr zu tun, um ihren kunden entgegenzukommen. die umwandlung von text in sprache kann ein ansprechendes erlebnis für das publikum bieten und zu erneuten besuchen anregen! der text-to-speech-dienst von gspeech bietet die möglichkeit, mit nur einem klick eine barrierefreiheitsfunktion in jede site einzufügen. der text-to-speech-dienst von gspeech implementiert die web content accessibility guidelines (wcag) in die site.
Schließen Sie den Kontextplayer
la tecnologia text-to-speech può creare contenuti più coinvolgenti per i clienti. converti i tuoi articoli, blog o qualsiasi contenuto in audio text-to-speech di alta qualità per gli utenti che preferiscono ascoltare anziché leggere. dimostra anche che sei disposto a fare uno sforzo in più per soddisfare i tuoi clienti. trasformare il testo in parlato può offrire un'esperienza coinvolgente per il pubblico, incoraggiando le visite di ritorno! il servizio text to speech di gspeech offre l'opportunità di aggiungere funzionalità di accessibilità in qualsiasi sito con un solo clic. il servizio text to speech di gspeech implementa le linee guida per l'accessibilità dei contenuti web (wcag) nel sito.
Chiudi lettore contestuale
технология преобразования текста в речь может создавать более привлекательный контент для клиентов. преобразуйте свои статьи, блог или любой контент в высококачественный текст в речь для пользователей, которые предпочитают слушать, а не читать. это также показывает, что вы готовы пройти лишнюю милю, чтобы удовлетворить своих клиентов. преобразование текста в речь может обеспечить увлекательный опыт для аудитории, поощряя повторные посещения! служба преобразования текста в речь от gspeech дает возможность добавить функцию доступности на любой сайт всего за один клик. служба преобразования текста в речь от gspeech реализует руководство по обеспечению доступности веб-контента (wcag) на сайте.
Закрыть контекстный проигрыватель
テキスト読み上げ技術により、顧客にとってより魅力的なコンテンツを作成できます。記事、ブログ、その他のコンテンツを高品質のテキスト読み上げオーディオに変換して、読むよりも聞くことを好むユーザーに対応します。また、顧客に対応するためにさらに努力する意思があることも示します。テキストを音声に変換すると、視聴者に魅力的な体験を提供でき、再訪問を促すことができます。gspeech のテキスト読み上げサービスでは、ワンクリックで任意のサイトにアクセシビリティ機能を追加できます。gspeech のテキスト読み上げサービスは、サイトに web コンテンツ アクセシビリティ ガイドライン (wcag) を実装します。
コンテキスト プレーヤーを閉じる
文本转语音技术可以为客户创建更具吸引力的内容。将您的文章、博客或任何内容转换为高质量的文本转语音音频，供喜欢聆听而非阅读的用户使用。这也表明您愿意付出更多努力来满足客户的需求。将文本转换为语音可以为观众提供引人入胜的体验，鼓励回访！gspeech 的文本转语音服务让您只需单击一下即可在任何站点中添加无障碍功能。gspeech 的文本转语音服务在站点中实施了 web 内容无障碍指南 (wcag)。
关闭上下文播放器
allowing people to converse with machines is a long-standing dream of human-computer interaction. the ability of computers to understand natural speech has been revolutionised in the last few years by the application of deep neural networks (e.g., google voice search). however, generating speech with computers — a process usually referred to as speech synthesis or text-to-speech (tts) — is still largely based on so-called concatenative tts, where a very large database of short speech fragments are recorded from a single speaker and then recombined to form complete utterances. this makes it difficult to modify the voice (for example switching to a different speaker, or altering the emphasis or emotion of their speech) without recording a whole new database. this has led to a great demand for parametric tts, where all the information required to generate the data is stored in the parameters of the model, and the contents and characteristics of the speech can be controlled via the inputs to the model. so far, however, parametric tts has tended to sound less natural than concatenative. existing parametric models typically generate audio signals by passing their outputs through signal processing algorithms known as vocoders. wavenet changes this paradigm by directly modeling the raw waveform of the audio signal, one sample at a time. as well as yielding more natural-sounding speech, using raw waveforms means that wavenet can model any kind of audio, including music.
Close context player
allowing people to converse with machines is a long-standing dream of human-computer interaction. the ability of computers to understand natural speech has been revolutionised in the last few years by the application of deep neural networks (e.g., google voice search). however, generating speech with computers — a process usually referred to as speech synthesis or text-to-speech (tts) — is still largely based on so-called concatenative tts, where a very large database of short speech fragments are recorded from a single speaker and then recombined to form complete utterances. this makes it difficult to modify the voice (for example switching to a different speaker, or altering the emphasis or emotion of their speech) without recording a whole new database. this has led to a great demand for parametric tts, where all the information required to generate the data is stored in the parameters of the model, and the contents and characteristics of the speech can be controlled via the inputs to the model. so far, however, parametric tts has tended to sound less natural than concatenative. existing parametric models typically generate audio signals by passing their outputs through signal processing algorithms known as vocoders. wavenet changes this paradigm by directly modeling the raw waveform of the audio signal, one sample at a time. as well as yielding more natural-sounding speech, using raw waveforms means that wavenet can model any kind of audio, including music.
Close context player
allowing people to converse with machines is a long-standing dream of human-computer interaction. the ability of computers to understand natural speech has been revolutionised in the last few years by the application of deep neural networks (e.g., google voice search). however, generating speech with computers — a process usually referred to as speech synthesis or text-to-speech (tts) — is still largely based on so-called concatenative tts, where a very large database of short speech fragments are recorded from a single speaker and then recombined to form complete utterances. this makes it difficult to modify the voice (for example switching to a different speaker, or altering the emphasis or emotion of their speech) without recording a whole new database. this has led to a great demand for parametric tts, where all the information required to generate the data is stored in the parameters of the model, and the contents and characteristics of the speech can be controlled via the inputs to the model. so far, however, parametric tts has tended to sound less natural than concatenative. existing parametric models typically generate audio signals by passing their outputs through signal processing algorithms known as vocoders. wavenet changes this paradigm by directly modeling the raw waveform of the audio signal, one sample at a time. as well as yielding more natural-sounding speech, using raw waveforms means that wavenet can model any kind of audio, including music.
Close context player
allowing people to converse with machines is a long-standing dream of human-computer interaction. the ability of computers to understand natural speech has been revolutionised in the last few years by the application of deep neural networks (e.g., google voice search). however, generating speech with computers — a process usually referred to as speech synthesis or text-to-speech (tts) — is still largely based on so-called concatenative tts, where a very large database of short speech fragments are recorded from a single speaker and then recombined to form complete utterances. this makes it difficult to modify the voice (for example switching to a different speaker, or altering the emphasis or emotion of their speech) without recording a whole new database. this has led to a great demand for parametric tts, where all the information required to generate the data is stored in the parameters of the model, and the contents and characteristics of the speech can be controlled via the inputs to the model. so far, however, parametric tts has tended to sound less natural than concatenative. existing parametric models typically generate audio signals by passing their outputs through signal processing algorithms known as vocoders. wavenet changes this paradigm by directly modeling the raw waveform of the audio signal, one sample at a time. as well as yielding more natural-sounding speech, using raw waveforms means that wavenet can model any kind of audio, including music.
Close context player
allowing people to converse with machines is a long-standing dream of human-computer interaction. the ability of computers to understand natural speech has been revolutionised in the last few years by the application of deep neural networks (e.g., google voice search). however, generating speech with computers — a process usually referred to as speech synthesis or text-to-speech (tts) — is still largely based on so-called concatenative tts, where a very large database of short speech fragments are recorded from a single speaker and then recombined to form complete utterances. this makes it difficult to modify the voice (for example switching to a different speaker, or altering the emphasis or emotion of their speech) without recording a whole new database. this has led to a great demand for parametric tts, where all the information required to generate the data is stored in the parameters of the model, and the contents and characteristics of the speech can be controlled via the inputs to the model. so far, however, parametric tts has tended to sound less natural than concatenative. existing parametric models typically generate audio signals by passing their outputs through signal processing algorithms known as vocoders. wavenet changes this paradigm by directly modeling the raw waveform of the audio signal, one sample at a time. as well as yielding more natural-sounding speech, using raw waveforms means that wavenet can model any kind of audio, including music.
Close context player
allowing people to converse with machines is a long-standing dream of human-computer interaction. the ability of computers to understand natural speech has been revolutionised in the last few years by the application of deep neural networks (e.g., google voice search). however, generating speech with computers — a process usually referred to as speech synthesis or text-to-speech (tts) — is still largely based on so-called concatenative tts, where a very large database of short speech fragments are recorded from a single speaker and then recombined to form complete utterances. this makes it difficult to modify the voice (for example switching to a different speaker, or altering the emphasis or emotion of their speech) without recording a whole new database. this has led to a great demand for parametric tts, where all the information required to generate the data is stored in the parameters of the model, and the contents and characteristics of the speech can be controlled via the inputs to the model. so far, however, parametric tts has tended to sound less natural than concatenative. existing parametric models typically generate audio signals by passing their outputs through signal processing algorithms known as vocoders. wavenet changes this paradigm by directly modeling the raw waveform of the audio signal, one sample at a time. as well as yielding more natural-sounding speech, using raw waveforms means that wavenet can model any kind of audio, including music.
Close context player
allowing people to converse with machines is a long-standing dream of human-computer interaction. the ability of computers to understand natural speech has been revolutionised in the last few years by the application of deep neural networks (e.g., google voice search). however, generating speech with computers — a process usually referred to as speech synthesis or text-to-speech (tts) — is still largely based on so-called concatenative tts, where a very large database of short speech fragments are recorded from a single speaker and then recombined to form complete utterances. this makes it difficult to modify the voice (for example switching to a different speaker, or altering the emphasis or emotion of their speech) without recording a whole new database. this has led to a great demand for parametric tts, where all the information required to generate the data is stored in the parameters of the model, and the contents and characteristics of the speech can be controlled via the inputs to the model. so far, however, parametric tts has tended to sound less natural than concatenative. existing parametric models typically generate audio signals by passing their outputs through signal processing algorithms known as vocoders. wavenet changes this paradigm by directly modeling the raw waveform of the audio signal, one sample at a time. as well as yielding more natural-sounding speech, using raw waveforms means that wavenet can model any kind of audio, including music.
Close context player
Select and listen
Welcome Message Demo
This page wants to play audio.
Play
Close