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Text to Speech


     Text-to-Speech (TTS) is a computer software that presents text auditorally. TTS is thought to circumvent the need to decode words by presenting them auditorally.  Most programs highlight text as it is being read out loud, thus allowing students to follow along. Depending on the specific program, there can also be an embedded dictionary that allows students to click on unfamiliar words and see the definition. Some softwares are also able to recognize and read scanned pages from a book. Other softwares have the ability to split the words into syllables and highlight specific parts of the speech when reading out the text. Using the software is quite easy, as the user simply has to highlight a section they want to read and then select ‘read’.


     There has been conflicting research on the benefits of TTS. For instance, Schmitt (2011) found that listening to text while reading it did not improve total reading comprehension compared to a silent reading condition. Furthermore, Meyer (2014) found no significant improvement in reading fluency, text comprehension, and time taken to complete the readings. 


     However, there have been more recent studies that provide strong evidence for the benefits of TTS. When 164 students in grade nine with reading disabilities used a TTS software for ten weeks, they showed significant improvements in reading comprehension and vocabulary, not only while using TTS, but also when reading from paper (Park et al, 2017). White (2014) observed increased motivation to read, improved reading comprehension and improved fluency on assessments when a group of students with dyslexia used a TTS software in a small-group setting for six weeks. Additionally, when a group of students in Taiwan used TTS to learn a list of words for a spelling bee, they were able to memorize approximately twelve more words using TTS; thus suggesting that TTS helps increase vocabulary for students that are learning English as a second language (Huang and Liao, 2015). Combined, these studies suggest that while text-to-speech may not have significant impacts for fluent readers, it can be very useful for users with deficits in decoding or reading fluency. 

Special Consideration: Workflow

To use TTS you’ll need documents in an electronic form. This means that the document has been uploaded to a computer in a digital format. This includes documents drafted on a computer (i.e., student assignments), or hard-copy documents that have been scanned into a computer (i.e., worksheets or textbook pages). If you are using a scanner to input documents into the computer, opt for one with Optical Character Recognition (OCR) technology. OCR is a tool that takes digital documents in non-readable formats, and transforms them into a Readable Format. This means that rather than scanning and uploading your document as a picture file, OCR technology will create a file in a Readable Format that your computer can recognize and interact with. Many scanners for physical documents have OCR built in, however some do not. When scanning, consult the product’s web page to check if it has built-in OCR. If the scanner doesn’t have a built in OCR, there are OCR softwares that can convert documents on your computer/mobile device into a Readable Format.

Once the document is on your computer, you must ensure the document has readable text. Some files have readable text already, whereas some are stored more like pictures and are therefore not readable. PDFs specifically are often stored in this type of in-accessible format. To check if a document is readable, try highlighting lines of text and copying and pasting them into a word processing program (e.g., Microsoft Word). If the text can be successfully copied and pasted, it is likely in a Readable Format. If a document is not in a Readable Format, you will need an optical character recognition (OCR) tool that converts non-readable documents into Readable Format. As mentioned above, this can be done during the scanning phase by using a scanner with OCR, or after the scanning phase using an OCR tech on your computer. To explore your OCR options, visit our OCR review page.

Research Rating: Due to the experimental nature of the information cited in this description this information is to be trusted as valid and reliable. 


  • Effective in circumventing problems for students with reading learning disabilities

  • Can be used regardless of impaired vision

  • Can assist writers in editing and proofreading texts



  • None


To Consider

  • Find the right voice. Having a high quality TTS voice will improve comprehension (Cunningham, 2011). To preview different voices, visit:

  • Control the speed at which the voice presents the text. Having the computer present between 140 and 180 words per minute is an optimal speed (Cunningham, 2003, Cunningham, 2011).

  • The program should have bi-modal reading ability, that is, have the computer highlight the presented word as it is presented out loud (Montali & Lewandowski, 1996).

  • Only select a small amount of text at any one time. Having too much text selected will lead to poor comprehension.

OS Compatibility
Internet Reliance
Optimized Use

Exact prices change frequently, which is why only approximate ranges are listed. 

$ - Under $5

$$ - Between $6 and $50

$$$ - Between $51 and $250

$$$$ - Over $250


Csapó, Á., Wersényi, G., Nagy, H., & Stockman, T. (2015). A survey of assistive technologies and applications for blind users on mobile platforms: a review and foundation for research. Journal on Multimodal User Interfaces, 9(4), 275-286.

Draffan, E. A., Evans, D. G., & Blenkhorn, P. (2007). Use of assistive technology by students with dyslexia in post-secondary education. Disability and Rehabilitation: Assistive Technology, 2(2), 105-116.

Forgrave, K. E. (2002). Assistive technology: Empowering students with learning disabilities. The Clearing House, 75(3), 122-126.

Huang, Y. C., Lioa, L. C. A Study of Text-to-Speech (TTS) in Children’s English Learning. Teaching English with Technology. 1, 14-30.

Meyer, N. K., & Bouck, E. C. (2014). The impact of text-to-speech on expository reading for adolescents with LD. Journal of Special Education Technology. 29(1), 21-33.

Meyer, N. K., & Bouck, E. C. (2014). The impact of text-to-speech on expository reading for adolescents with LD. Journal of Special Education Technology, 29(1), 21-33.

Park, H. J., Takahashi, K., Roberts, K.D., Delise, R., Delise, Danielle. (2017). Effects of text-to-speech software use on the reading proficiency of high school struggling readers. Assistive Technology. 29(3), 146-152.

Schmitt, A. J., Hale, A. D., McCallum, E., & Mauck, B. (2011). Accommodating remedial readers in the general education setting: Is listening‐while‐reading sufficient to improve factual and inferential comprehension? Psychology in the Schools, 48(1), 37-45. 

Written by Harrison McNaughtan and Rudra Patel, Last Revision March 2019

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