Dataset · Typing and writing speed
Speech vs Typing Speed: Text Entry Rates Compared
How fast can people enter text by keyboard, touchscreen, handwriting, voice and other methods?
Speech recognition is the fastest everyday way to enter text, with a median of 138 words per minute, against 51.6 on a computer keyboard and 35.2 on a phone keyboard. Only stenography, a trained professional skill, is faster, at a median of 355 words per minute.
57 data points from 25 sourcesUpdated October 19, 2026Free to reuse under CC BY 4.0
138words per minute
In the text entry speed by input method dataset, the 2 published figures for “Speech recognition” have a median of 138 words per minute, ranging from 123 to 153.
How it is calculated
51.6words per minute
In the text entry speed by input method dataset, the 19 published figures for “Computer keyboard” have a median of 51.6 words per minute, ranging from 15 to 163.
How it is calculated
35.2words per minute
In the text entry speed by input method dataset, the 22 published figures for “Phone touchscreen keyboard” have a median of 35.2 words per minute, ranging from 1.6 to 52.
How it is calculated
355words per minute
In the text entry speed by input method dataset, the 2 published figures for “Stenography” have a median of 355 words per minute, ranging from 350 to 360.
How it is calculated
Speech recognition is the fastest everyday way to get text onto a screen. The dataset's speech figures have a median of 138 words per minute 1. A computer keyboard has a median of 51.6 2, a phone keyboard 35.2 3, and handwriting on paper 19.4 4. Stenography, which takes years of training, reaches a median of 355 5.
The speech evidence is thin, though. This page rests on 57 data points 6 from 25 sources 7, and most of them describe typing. Speech has only two rows, both from one study.
Speech beats the phone keyboard by a wide margin in the lab
The cleanest comparison in the data comes from one controlled study in which the same people entered short messages by voice and by keyboard. In English on an iPhone, speech reached 153 words per minute 8, while the built-in keyboard reached 52 9. In Mandarin Chinese, speech reached 123 10 and the Pinyin keyboard 43 11.
The gap is large in both languages, so it does not look like a quirk of English.
| Who | Task | Includes fixing errors | People | Entry speed (WPM) | Source |
|---|---|---|---|---|---|
| Lab participants, short messages | Copying text | Yes | 153 | Ruan et al., 2018 8 | |
| Lab participants, short messages | Copying text | Not stated | 123 | Ruan et al., 2018 10 |
These figures count copying short phrases in a quiet room, with an older recognizer. They do not include the time spent fixing a dictated draft, long documents or noisy places. Treat them as the speed of getting words out, not of finishing a document. Our overview of dictation covers what happens after the words appear.
Phone typing is slower than desktop typing, and it varies with how you hold the phone
The phone keyboard has the most rows in the dataset. The largest is an online study of volunteers typing on their own phones, with a mean of 36.2 words per minute 12. A field study, in which people typed in their own apps, found 32.1 13. The two designs differ, yet the results sit close together.
Within phone typing, how you hold the device makes a visible difference. People who typed with two fingers averaged 37.7 14, and two thumbs reached 38.02 15. Age also shows. The fastest age group, the teenagers, averaged 39.6 16, and the oldest adult group averaged 26.3 17. Young children were slowest, at 24.3 18.
Language experience adds a further effect. Native English speakers averaged 37.8 19, while people who never type in English averaged 25.6 20 on English test sentences.
Screen reader users form a separate case. Blind participants averaged 7.5 words per minute 21 on a QWERTY keyboard with VoiceOver, and another small study measured 1.87 22 without word prediction. These samples are small and the two results differ greatly, so they show the range of experience more than a typical speed.
Swipe typing and word prediction did not make people faster
Gesture typing is often described as a speed feature. In the data, people who reported swipe typing averaged 32.2 words per minute 23, which was not faster than people who used no intelligent text entry feature. Word prediction alone gave 32.8 24, also no better. In the blind-user study, prediction did not help either: 1.63 25 with it, and the difference was not significant.
Do not read this as proof that these features slow people down. The use was self-reported, not assigned, so faster typists may simply need them less.
Computer keyboards span a wide range, and the average depends on who took the test
The computer keyboard has the most rows after the phone, and the widest spread. At the slow end, a school typing course control group reached 15 words per minute 26 after training. At the fast end, a championship finalist typed a standard text at 163 27, an unofficial record from a single race.
Between those extremes, the large online tests agree with each other. A very large online test averaged 51.56 28. Workers surveyed by Typing.com who used all their fingers averaged 54.6 29, and a lab study put standard touch typists at 79.99 30.
Another large source reports lower. Ratatype's test takers had a median in the range Ratatype rounds to 30 to 40 31. Both groups chose to take an online test, so the difference probably reflects who takes which test, not a real conflict. Our guide to typing speed covers population averages in more depth.
Touch typing matters less than its reputation
Typists who never learned touch typing did not lose much. In one transcription task, touch typists averaged 57.8 words per minute 32 and non-touch typists 58.93 33, a difference the authors found not significant. Another lab study found a clear edge for touch typists, 79.99 against 65.63 for nonstandard typists 34. The studies disagree, and the likely reason is who was recruited: the first group of non-touch typists were already fast, with a wide range of speeds.
Health shows in the numbers too. Patients typed at 49.7 35 before carpal tunnel surgery, slowed to 45.2 36 soon after, and reached 53.5 37 about three months later.
Handwriting is the slowest method for most people
Handwriting on paper has a median of 19.4 words per minute 4. University students copying text averaged 22.85 38, and a school norm for the end of middle school is 16 39. Both are copying tasks, which are usually faster than composing, so writing your own thoughts by hand is probably slower still.
The dataset holds no rows for handwriting recognition, braille input or eye typing. That is a gap in the evidence, not evidence that these methods are slow.
Brain-computer interfaces now match a good typist, with caveats
The brain-computer interface median is 52.9 words per minute 40. Individual rows run from 30.6 41 for decoded vocalized speech to 78 42 for attempted silent speech. A participant with ALS reached 62 43 and later averaged 56 44 at home.
Each of these is one person with an implanted device, and the faster results carried high word error rates. This is a tool for people who cannot speak or type, not a comparison for general readers. The same applies to other assistive methods: a head mouse reached 6.3 45 for one participant, and a joystick method reached 14.9 46 after practice.
Stenography is fastest, but the figures are records
Two stenography figures exist: 350 words per minute 47 for an early shorthand record, and 360 48 for a realtime record. Both are single record attempts, one a short burst, so they show what is possible, not what a working reporter sustains daily.
What the data cannot tell you
The rows are not a random sample of anyone. Many come from volunteers who chose to take an online test, which tends to raise averages. Tasks differ: copying is faster than composing, and most rows are copying or unspecified. Few rows say whether time spent correcting errors is counted, so a figure may describe raw entry, not finished text. Several rows come from older devices or an older recognizer, and there is no like-for-like study that measures speech, phone and desktop typing for the same people composing real documents.
The medians also mix very different groups. The phone median blends children, older adults and blind users, and the speech median is two numbers from one study.
What this means for choosing how to write
If you are on a phone, voice is the clearest gain in the data, since the phone keyboard is where typists are slowest relative to what speech reaches. On a computer, a typical keyboard speed is already competitive with writing by hand, and learning to touch type shows an uneven benefit in these studies. If you spend a lot of time on drafts, try dictation for the first pass and keep the keyboard for editing, because the lab figures do not include editing time. Handwriting is the slowest option in the data, so choose it for reasons other than speed.
Pick a method for your task and test it on your own writing for a week. A published average will not tell you how fast you will be.
Evidence
Every number on this page, with where it comes from. Open a fact to see the exact words in its source.
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- 6.The text entry speed by input method dataset holds 57 data points, each a published figure traced to its source.
Calculated from 57 other facts
- 7.The text entry speed by input method dataset draws on 25 distinct sources.
Calculated from 57 other facts
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- 12.In an online study of 37,370 volunteers typing on their own phones, the average speed was 36.2 words per minute, with 2.3 percent uncorrected errors.
Kseniia Palin et al., Proceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI 2019), 2019 · Original
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- 14.In the Palin study, participants who reported using two fingers averaged 37.7 words per minute, significantly faster than the 29.2 of those who used only one finger.
Kseniia Palin et al., Proceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI 2019), 2019 · Original
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- 23.In the Palin study, people who reported gesture (swipe) typing averaged 32.2 words per minute overall, against 34.8 for people who used no intelligent text entry feature.
Kseniia Palin et al., Proceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI 2019), 2019 · Original
- 24.In the Palin study, people who reported word prediction alone averaged 32.8 words per minute, against 34.8 for people who used no intelligent text entry feature.
Kseniia Palin et al., Proceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI 2019), 2019 · Original
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- 46.In a user study of the TwoStick joystick text entry method, entry rates started at 4.3 words per minute and reached 14.9 words per minute after five hours of practice, as reported by Castellucci and MacKenzie in 2008.
Steven J. Castellucci and I. Scott MacKenzie, Extended Abstracts of the ACM Conference on Human Factors in Computing Systems (CHI 2008), 2008 · Original
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The data behind these numbers
Every data point
Each row is one published figure for one group, in words per minute. The row opens its fact page with the exact words of the source; the source opens the original.
| Source | ||||||||
|---|---|---|---|---|---|---|---|---|
| Wrona 2010, standard text | Computer keyboard | Championship finalist, live race | Mixed or unspecified | Not stated | 2010 | 163 | Wikipedia | |
| Logan et al. 2016, standard typists | Computer keyboard | Standard touch typists, lab study | Mixed or unspecified | Not stated | 24 | 2016 | 80 | Logan et al., 2016 |
| Logan et al. 2016, nonstandard typists | Computer keyboard | Nonstandard typists, lab study | Mixed or unspecified | Not stated | 24 | 2016 | 65.6 | Logan et al., 2016 |
| Typing.com, mainly did not look down | Computer keyboard | Full-time workers who type on computers at work, mainly did not look down at the keyboard | Not stated | 61 | Typing.com | |||
| Feit et al. 2016, non-touch | Computer keyboard | Non-touch typists | Copying text | Not stated | 2016 | 58.9 | Feit et al., 2016 | |
| Feit et al. 2016, touch typists | Computer keyboard | Touch typists | Copying text | Not stated | 2016 | 57.8 | Feit et al., 2016 | |
| Typing.com, 5 to 9 fingers | Computer keyboard | Full-time workers who type on computers at work, 5 to 9 fingers | Not stated | 54.7 | Typing.com | |||
| Typing.com, all 10 fingers | Computer keyboard | Full-time workers who type on computers at work, all 10 fingers | Not stated | 54.6 | Typing.com | |||
| Zumsteg et al. 2016, 12 weeks after | Computer keyboard | Patients 12 weeks after open carpal tunnel release | Mixed or unspecified | Not stated | 2016 | 53.5 | Zumsteg et al., 2016 | |
| 136M keystrokes, CHI 2018 | Computer keyboard | Online typing test volunteers | Mixed or unspecified | Not stated | 168000 | 2018 | 51.6 | Dhakal et al., 2018 |
| Zumsteg et al. 2016, before surgery | Computer keyboard | Patients before open carpal tunnel release | Copying text | Not stated | 27 | 2016 | 49.7 | Zumsteg et al., 2016 |
| Zumsteg et al. 2016, post-surgery | Computer keyboard | Patients 8 to 10 days after open carpal tunnel release | Mixed or unspecified | Not stated | 27 | 2016 | 45.2 | Zumsteg et al., 2016 |
| Suhm et al. 1999, fast typists | Computer keyboard | Fast typists | Mixed or unspecified | Not stated | 5 | 1999 | 40 | Suhm et al., 1999 |
| Typing.com, mainly looked down | Computer keyboard | Full-time workers who type on computers at work, mainly looked at the keyboard | Not stated | 39.5 | Typing.com | |||
| Typing.com, male baby boomers | Computer keyboard | Full-time workers who type on computers at work, male baby boomers | Not stated | 38 | Typing.com | |||
| Ratatype 2026 median | Computer keyboard | People who took a free typing test on Ratatype's website | Not stated | 506024 | 2026 | 30 to 40 | Ratatype, 2026 | |
| UCT dissertation 2017, gamified | Computer keyboard | Grade 11 learners, typing course with game elements | Mixed or unspecified | Not stated | 2017 | 25 | Chomunorwa, 2017 | |
| Japanese students, desktop PC | Computer keyboard | Japanese university students | Copying text | Yes | 24 | 23 | Houser et al. | |
| UCT dissertation 2017, control | Computer keyboard | Control group, typing course without game elements | Mixed or unspecified | Not stated | 2017 | 15 | Chomunorwa, 2017 | |
| Ruan et al. 2018, English keyboard | Phone touchscreen keyboard | Lab participants, short messages | Copying text | Yes | 2016 | 52 | Ruan et al., 2018 | |
| Ruan et al. 2018, Mandarin keyboard | Phone touchscreen keyboard | Lab participants, short messages | Copying text | Not stated | 2016 | 43 | Ruan et al., 2018 | |
| Palin et al. 2019, ages 10-19 | Phone touchscreen keyboard | Online volunteers aged 10 to 19 | Mixed or unspecified | Not stated | 2019 | 39.6 | Palin et al., 2019 | |
| Palin et al. 2019, U.S. ages 20-29 | Phone touchscreen keyboard | U.S. volunteers aged 20 to 29 | Mixed or unspecified | Not stated | 2019 | 39 | Palin et al., 2019 | |
| Palin et al. 2019, two thumbs | Phone touchscreen keyboard | Online volunteers who typed with two thumbs | Mixed or unspecified | Not stated | 2019 | 38 | Palin et al., 2019 | |
| Palin et al. 2019, native English | Phone touchscreen keyboard | Online volunteers, native English users | Mixed or unspecified | Not stated | 2019 | 37.8 | Palin et al., 2019 | |
| Palin et al. 2019, two fingers | Phone touchscreen keyboard | Online volunteers who used two fingers | Mixed or unspecified | Not stated | 2019 | 37.7 | Palin et al., 2019 | |
| Palin et al. 2019, U.S. men | Phone touchscreen keyboard | U.S. male volunteers | Mixed or unspecified | Not stated | 2019 | 37.4 | Palin et al., 2019 | |
| Palin et al. 2019, ages 20-29 | Phone touchscreen keyboard | Online volunteers aged 20 to 29, full sample | Mixed or unspecified | Not stated | 2019 | 36.5 | Palin et al., 2019 | |
| Palin et al. 2019, all phones | Phone touchscreen keyboard | Online volunteers, full sample | Copying text | Not stated | 37370 | 2019 | 36.2 | Palin et al., 2019 |
| Palin et al. 2019, touch typing course | Phone touchscreen keyboard | Online volunteers with a desktop touch typing course | Mixed or unspecified | Not stated | 2019 | 35.7 | Palin et al., 2019 | |
| Palin et al. 2019, U.S. women | Phone touchscreen keyboard | U.S. female volunteers | Mixed or unspecified | Not stated | 2019 | 34.6 | Palin et al., 2019 | |
| Palin et al. 2019, prediction only | Phone touchscreen keyboard | Online volunteers who used word prediction alone | Mixed or unspecified | Not stated | 2019 | 32.8 | Palin et al., 2019 | |
| Palin et al. 2019, ages 30-39 | Phone touchscreen keyboard | Online volunteers aged 30 to 39, full sample | Mixed or unspecified | Not stated | 2019 | 32.2 | Palin et al., 2019 | |
| Buschek et al. 2018, field study | Phone touchscreen keyboard | Participants typing in their own apps | Mixed or unspecified | Not stated | 30 | 2018 | 32.1 | Buschek et al., 2018 |
| Palin et al. 2019, ages 40-49 | Phone touchscreen keyboard | Online volunteers aged 40 to 49, full sample | Mixed or unspecified | Not stated | 2019 | 28.9 | Palin et al., 2019 | |
| Palin et al. 2019, ages 50-59 | Phone touchscreen keyboard | Online volunteers aged 50 to 59, full sample | Mixed or unspecified | Not stated | 2019 | 26.3 | Palin et al., 2019 | |
| Palin et al. 2019, never English | Phone touchscreen keyboard | Online volunteers who never type in English | Mixed or unspecified | Not stated | 2019 | 25.6 | Palin et al., 2019 | |
| Palin et al. 2019, under 10 | Phone touchscreen keyboard | Online volunteers under 10, full sample | Mixed or unspecified | Not stated | 2019 | 24.3 | Palin et al., 2019 | |
| Gaines et al. 2023, QWERTY + VoiceOver | Phone touchscreen keyboard | Blind participants, longitudinal study | Mixed or unspecified | Not stated | 12 | 2023 | 7.5 | Gaines, 2023 |
| Alnfiai et al. 2024, no prediction | Phone touchscreen keyboard | Blind participants using a screen reader | Mixed or unspecified | Not stated | 2024 | 1.9 | Alnfiai et al., 2024 | |
| Alnfiai et al. 2024, with prediction | Phone touchscreen keyboard | Blind adults using a screen reader | Mixed or unspecified | Not stated | 11 | 2024 | 1.6 | Alnfiai et al., 2024 |
| Palin et al. 2019, swipe typing | Gesture or swipe typing | Phone typists who reported swipe typing | Mixed or unspecified | Not stated | 2019 | 32.2 | Palin et al., 2019 | |
| Franzsen et al. 2014, copying | Handwriting on paper | University students in South Africa | Copying text | Not stated | 300 | 2014 | 22.9 | Franzsen et al., 2014 |
| Amundson 1995 norm, middle school | Handwriting on paper | Children at the end of middle school (compiled norm) | Copying text | Not stated | 1995 | 16 | Schools | |
| Ruan et al. 2018, English speech | Speech recognition | Lab participants, short messages | Copying text | Yes | 2016 | 153 | Ruan et al., 2018 | |
| Ruan et al. 2018, Mandarin speech | Speech recognition | Lab participants, short messages | Copying text | Not stated | 2016 | 123 | Ruan et al., 2018 | |
| Kislingbury, realtime record | Stenography | One person, record attempt | Copying text | Not stated | 1 | 2004 | 360 | Guinness World Records |
| Behrin 1922, Pitman record | Stenography | Nathan Behrin, record holder | Mixed or unspecified | Not stated | 1922 | 350 | Wikipedia, the free encyclopedia | |
| Silent speech neuroprosthesis 2023 | Brain-computer interface | One participant, attempted silent speech | Mixed or unspecified | Not stated | 1 | 2023 | 78 | Metzger et al., 2023 |
| Speech neuroprosthesis 2023 | Brain-computer interface | One participant with ALS | Mixed or unspecified | Not stated | 1 | 2023 | 62 | Willett et al., 2023 |
| Card et al. 2026, home use | Brain-computer interface | One participant with ALS, at home | Mixed or unspecified | Not stated | 1 | 2026 | 56 | Card et al., 2026 |
| Card et al. 2026, silent speech | Brain-computer interface | One participant, silent speech | Copying text | Not stated | 1 | 2026 | 49.7 | Card et al., 2026 |
| Card et al. 2024, speech copy | Brain-computer interface | One BrainGate participant | Copying text | Not stated | 1 | 2024 | 31.6 | Card et al., 2024 |
| Card et al. 2026, vocalized speech | Brain-computer interface | One participant, vocalized speech | Copying text | Not stated | 1 | 2026 | 30.6 | Card et al., 2026 |
| Japanese students, cellphone | Other | Japanese university students | Copying text | Not stated | 24 | 17 | Houser et al. | |
| Castellucci et al. 2007, 5 h practice | Other | Participants after five hours of practice | Mixed or unspecified | Not stated | 2007 | 14.9 | Castellucci et al., 2008 | |
| Card et al. 2024, head mouse | Other | One BrainGate participant | Mixed or unspecified | Not stated | 1 | 2024 | 6.3 | Card et al., 2024 |
57 rows. Open a row for the exact words of its source.
Calculated from the rows
Every statistic is calculated by code from the rows above. Open one to see the exact values it summarises.
- 51.6 words per minuteIn the text entry speed by input method dataset, the 19 published figures for “Computer keyboard” have a median of 51.6 words per minute, ranging from 15 to 163.Calculated from other facts
- 35.2 words per minuteIn the text entry speed by input method dataset, the 22 published figures for “Phone touchscreen keyboard” have a median of 35.2 words per minute, ranging from 1.6 to 52.Calculated from other facts
- 19.4 words per minuteIn the text entry speed by input method dataset, the 2 published figures for “Handwriting on paper” have a median of 19.4 words per minute, ranging from 16 to 22.9.Calculated from other facts
- 138 words per minuteIn the text entry speed by input method dataset, the 2 published figures for “Speech recognition” have a median of 138 words per minute, ranging from 123 to 153.Calculated from other facts
- 355 words per minuteIn the text entry speed by input method dataset, the 2 published figures for “Stenography” have a median of 355 words per minute, ranging from 350 to 360.Calculated from other facts
- 52.9 words per minuteIn the text entry speed by input method dataset, the 6 published figures for “Brain-computer interface” have a median of 52.9 words per minute, ranging from 30.6 to 78.Calculated from other facts
- 14.9 words per minuteIn the text entry speed by input method dataset, the 3 published figures for “Other” have a median of 14.9 words per minute, ranging from 6.3 to 17.Calculated from other facts
- 57 data pointsThe text entry speed by input method dataset holds 57 data points, each a published figure traced to its source.Calculated from other facts
- 25 sourcesThe text entry speed by input method dataset draws on 25 distinct sources.Calculated from other facts
How this dataset is built
- What counts as a row
- Measured text entry rates in words per minute for any input method, from controlled studies or published evaluations that state who was measured and how. Studies that compare two methods with the same people contribute one row per method.
- What does not
- Theoretical maximums, vendor claims without a published measurement, and speaking rates without text entry (in the speaking rate dataset instead).
- How rows are found and checked
- Rows come from the facts already cited across the library and from a structured search of human-computer interaction research (OpenAlex and Semantic Scholar). Each figure is stored as a fact with the exact words of its source, checked automatically against the live page.
- What the data cannot tell you
- Methods are measured in different studies with different people, phrases and error handling. A direct comparison is only fair within one study; the medians show the typical reported figure per method.
The search record
470
works found by the searches below
139
report a figure in the dataset's terms
0
read and judged by a researcher
0
kept, with their figures checked
The 20 searches, last run October 19, 2026
- OpenAlex: “text entry rate words per minute speech recognition keyboard comparison”, 50 results
- arXiv: “text entry rate words per minute speech recognition keyboard comparison”, 5 results
- OpenAlex: “speech input versus typing speed study”, 50 results
- arXiv: “speech input versus typing speed study”, 0 results
- OpenAlex: “touchscreen keyboard text entry words per minute”, 50 results
- arXiv: “touchscreen keyboard text entry words per minute”, 2 results
- OpenAlex: “handwriting speed words per minute adults”, 50 results
- Semantic Scholar: “handwriting speed words per minute adults”, 40 results
- arXiv: “handwriting speed words per minute adults”, 0 results
- OpenAlex: “stenography words per minute”, 50 results
- arXiv: “stenography words per minute”, 0 results
- OpenAlex: “eye typing words per minute”, 50 results
- Semantic Scholar: “eye typing words per minute”, 40 results
- arXiv: “eye typing words per minute”, 5 results
- OpenAlex: “brain computer interface typing speed words per minute”, 50 results
- arXiv: “brain computer interface typing speed words per minute”, 5 results
- OpenAlex: “gesture keyboard text entry rate”, 50 results
- arXiv: “gesture keyboard text entry rate”, 1 results
- OpenAlex: “braille text entry speed”, 50 results
- arXiv: “braille text entry speed”, 0 results
The whole method, from search to calculation, is on the research data page.
Cite and reuse
You may copy, share and adapt this dataset for any purpose, including commercially, if you credit it with a link. Quoted passages remain their authors' words: cite the original source for those.
Yap (2026). Text entry speed by input method [Data set]. https://yapapp.cc/data/text-entry-methods
License: CC BY 4.0.
Pages built on this data
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- How do blind people type on a computer?
- Text Expanders and Autocomplete: Type Less, Not Faster
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- Phone Typing Speed: How Fast People Type on Phones
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- The Future of Typing: Voice, AI and the Keyboard
- How fast can a brain-computer interface type?
- What is silent speech, and can you dictate without speaking aloud?
- How can you type faster on a PS5 or Xbox?
- Typing Speed: Average WPM and How to Type Faster
- Touch Typing: What It Is and How to Learn It
- Voice Coding: How to Program by Voice
- Do pianists and gamers type faster?
- Does typing speed matter in coding?
- How can you type Japanese faster?
- Is 60 words per minute a good typing speed?
- Typing Speed Statistics: Average WPM by Group
- Dictation for Work: Doctors, Lawyers, Writers, Students
- Writing Speed: Words per Minute by Hand and per Day
- How long does it take to write 1,000 words?
- Is it better to take notes by hand or on a laptop?
- Is typing faster than writing by hand?
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Read the overview: Typing Speed: Average WPM and How to Type Faster