Mexico is the country with the largest number of native Spanish speakers in the world. As of 2024, 132.5 million people in Mexico spoke Spanish with a native command of the language. Colombia was the nation with the second-highest number of native Spanish speakers, at around 52.7 million. Spain came in third, with 48 million, and Argentina fourth, with 46 million. Spanish, a world language As of 2023, Spanish ranked as the fourth most spoken language in the world, only behind English, Chinese, and Hindi, with over half a billion speakers. Spanish is the official language of over 20 countries, the majority on the American continent, nonetheless, it's also one of the official languages of Equatorial Guinea in Africa. Other countries have a strong influence, like the United States, Morocco, or Brazil, countries included in the list of non-Hispanic countries with the highest number of Spanish speakers. The second most spoken language in the U.S. In the most recent data, Spanish ranked as the language, other than English, with the highest number of speakers, with 12 times more speakers as the second place. Which comes to no surprise following the long history of migrations from Latin American countries to the Northern country. Moreover, only during the fiscal year 2022. 5 out of the top 10 countries of origin of naturalized people in the U.S. came from Spanish-speaking countries.

In 2025, there were around 1.53 billion people worldwide who spoke English either natively or as a second language, slightly more than the 1.18 billion Mandarin Chinese speakers at the time of survey. Hindi and Spanish accounted for the third and fourth most widespread languages that year. Languages in the United States The United States does not have an official language, but the country uses English, specifically American English, for legislation, regulation, and other official pronouncements. The United States is a land of immigration, and the languages spoken in the United States vary as a result of the multicultural population. The second most common language spoken in the United States is Spanish or Spanish Creole, which over than 43 million people spoke at home in 2023. There were also 3.5 million Chinese speakers (including both Mandarin and Cantonese),1.8 million Tagalog speakers, and 1.57 million Vietnamese speakers counted in the United States that year. Different languages at home The percentage of people in the United States speaking a language other than English at home varies from state to state. The state with the highest percentage of population speaking a language other than English is California. About 45 percent of its population was speaking a language other than English at home in 2023.

Language spoken at home and the ability to speak English for the population age 5 and over as reported by the US Census Bureau's, American Community Survey (ACS) 5-year estimates table C16001.

Language questions were only asked of persons 5 years and older. The language question is about current use of a non-English language at home, not about ability to speak another language or the use of such a language in the past or elsewhere. People who speak a language other than English outside of the home are not reported as speaking a language other than English. Respondents that spoke a language other than English at home, where also asked whether they could speak English "very well" or less than "very well. See how the Census Bureau measures Language Use for more information at https://www.census.gov/topics/population/language-use/about.html.

Source: U.S. Census Bureau; 2013-2017 American Community Survey 5-Year Estimates, Table C16001.

As of February 2025, English was the most popular language for web content, with over 49.4 percent of websites using it. Spanish ranked second, with six percent of web content, while the content in the German language followed, with 5.6 percent. English as the leading online language United States and India, the countries with the most internet users after China, are also the world's biggest English-speaking markets. The internet user base in both countries combined, as of January 2023, was over a billion individuals. This has led to most of the online information being created in English. Consequently, even those who are not native speakers may use it for convenience. Global internet usage by regions As of October 2024, the number of internet users worldwide was 5.52 billion. In the same period, Northern Europe and North America were leading in terms of internet penetration rates worldwide, with around 97 percent of its populations accessing the internet.

This data collection is a component of Summary Tape File (STF) 3, which consists of four sets of data files containing detailed tabulations of the nation's population and housing characteristics produced from the 1980 Census. The STF 3 files contain sample data inflated to represent the total United States population. The files also contain 100-percent counts and unweighted sample counts of persons and housing units. All files in the STF 3 series are identical, containing 321 substantive data variables organized in the form of 150 "tables," as well as standard geographic identification variables. Population items tabulated for each person include demographic data and information on schooling, Spanish origin, language spoken at home and ability to speak English, labor force status in 1979, residency in 1975, number of children ever born, means of transportation to work, current occupation, industry, and 1979 details on occupation, hours worked, and income. Housing items include size and condition of the housing unit as well as information on value, age, water, sewage and heating, number of vehicles, and monthly owner costs (e.g., sum of payments for real estate taxes, property insurance, utilities, and regular mortgage payments). Selected aggregates and medians are also provided. Each dataset in STF 3 provides different geographic coverage. Summary Tape File 3B provides summaries for each 5-digit ZIP-code area within a state, and for 5-digit ZIP-code areas within states that were contained within Standard Metropolitan Statistical Areas (SMSAs), portions of SMSAs, or within counties, county portions, or county equivalents. All persons and housing units in the United States were sampled. Population and housing items include household relationship, sex, race, age, marital status, Hispanic origin, number of units at address, complete plumbing facilities, number of rooms, whether owned or rented, vacancy status, and value for noncondominiums. The Census Bureau's machine-readable data dictionary for STF 3 is also available through CENSUS OF POPULATION AND HOUSING, 1980 [UNITED STATES]: CENSUS SOFTWARE PACKAGE (CENSPAC) VERSION 3.2 WITH STF4 DATA DICTIONARIES (ICPSR 7789), the software package designed specifically by the Census Bureau for use with the 1980 Census data files. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR -- https://doi.org/10.3886/ICPSR08318.v1. We highly recommend using the ICPSR version as they made this dataset available in multiple data formats.

Emotion expression is an essential part of human interaction. The same text can hold different meanings when expressed with different emotions. Thus understanding the text alone is not enough for getting the meaning of an utterance. Acted and natural corpora have been used to detect emotions from speech. Many speech databases for different languages including English, German, Chinese, Japanese, Russian, Italian, Swedish and Spanish exist for modeling emotion recognition. Since there is no reported reference of an available Arabic corpus, we decided to collect the first Arabic Natural Audio Dataset (ANAD) to recognize discrete emotions.

Embedding an effective emotion detection feature in speech recognition system seems a promising solution for decreasing the obstacles faced by the deaf when communicating with the outside world. There exist several applications that allow the deaf to make and receive phone calls normally, as the hearing-impaired individual can type a message and the person on the other side hears the words spoken, and as they speak, the words are received as text by the deaf individual. However, missing the emotion part still makes these systems not hundred percent reliable. Having an effective speech to text and text to speech system installed in their everyday life starting from a very young age will hopefully replace the human ear. Such systems will aid deaf people to enroll in normal schools at very young age and will help them to adapt better in classrooms and with their classmates. It will help them experience a normal childhood and hence grow up to be able to integrate within the society without external help.

Eight videos of live calls between an anchor and a human outside the studio were downloaded from online Arabic talk shows. Each video was then divided into turns: callers and receivers. To label each video, 18 listeners were asked to listen to each video and select whether they perceive a happy, angry or surprised emotion. Silence, laughs and noisy chunks were removed. Every chunk was then automatically divided into 1 sec speech units forming our final corpus composed of 1384 records.

Twenty five acoustic features, also known as low-level descriptors, were extracted. These features are: intensity, zero crossing rates, MFCC 1-12 (Mel-frequency cepstral coefficients), F0 (Fundamental frequency) and F0 envelope, probability of voicing and, LSP frequency 0-7. On every feature nineteen statistical functions were applied. The functions are: maximum, minimum, range, absolute position of maximum, absolute position of minimum, arithmetic of mean, Linear Regression1, Linear Regression2, Linear RegressionA, Linear RegressionQ, standard Deviation, kurtosis, skewness, quartiles 1, 2, 3 and, inter-quartile ranges 1-2, 2-3, 1-3. The delta coefficient for every LLD is also computed as an estimate of the first derivative hence leading to a total of 950 features.

I would have never reached that far without the help of my supervisors. I warmly thank and appreciate Dr. Rached Zantout, Dr. Lama Hamandi, and Dr. Ziad Osman for their guidance, support and constant supervision.

This dataset includes the primary language of newly Medi-Cal eligible individuals who identified their primary language as English, Spanish, Vietnamese, Mandarin, Cantonese, Arabic, Other Non-English, Armenian, Russian, Farsi, Korean, Tagalog, Other Chinese Languages, Hmong, Cambodian, Portuguese, Lao, French, Thai, Japanese, Samoan, Other Sign Language, American Sign Language (ASL), Turkish, Ilacano, Mien, Italian, Hebrew, and Polish, by reporting period. The primary language data is from the Medi-Cal Eligibility Data System (MEDS) and includes eligible individuals without prior Medi-Cal eligibility. This dataset is part of the public reporting requirements set forth in California Welfare and Institutions Code 14102.5.

In 2019, about 12.08 million children were speaking another language other than English at home in the United States. This number is fairly consistent with the previous year, where 12.13 million children spoke another language at home.

This statistic shows a breakdown of the Hong Kong population by language, based on the latest available census data from 2021. Based on this data, around *** percent of Hong Kong inhabitants were English speakers.

As of 2019, *** million middle school students in Italy studied English as a foreign language. In elementary school, the number of pupils learning English added up to *** million. According to data from 2019, almost all students in Italy learned English in school. French and Spanish were the second and third most tought foreign languages in Italian schools.