chinese speaker
Improve Bilingual TTS Using Dynamic Language and Phonology Embedding
Yang, Fengyu, Luan, Jian, Wang, Yujun
In most cases, bilingual TTS needs to handle three types of input scripts: first language only, second language only, and second language embedded in the first language. In the latter two situations, the pronunciation and intonation of the second language are usually quite different due to the influence of the first language. Therefore, it is a big challenge to accurately model the pronunciation and intonation of the second language in different contexts without mutual interference. This paper builds a Mandarin-English TTS system to acquire more standard spoken English speech from a monolingual Chinese speaker. We introduce phonology embedding to capture the English differences between different phonology. Embedding mask is applied to language embedding for distinguishing information between different languages and to phonology embedding for focusing on English expression. We specially design an embedding strength modulator to capture the dynamic strength of language and phonology. Experiments show that our approach can produce significantly more natural and standard spoken English speech of the monolingual Chinese speaker. From analysis, we find that suitable phonology control contributes to better performance in different scenarios.
- Asia > South Korea > Gyeonggi-do > Suwon (0.04)
- Asia > China > Beijing > Beijing (0.04)
Self-awareness in AI
What does being self-aware mean? Do we have self-aware robots? Both of these are key questions in the field of artificial intelligence, and questions that will be covered in this article. I will also explain the difference between a robot and AI, what self-awareness is, and some examples of self-awareness in robots. Robotics and artificial intelligence (AI) are two separate fields of engineering; a robot is a machine, whereas an AI is a program.
- Information Technology > Artificial Intelligence > Robots (1.00)
- Information Technology > Artificial Intelligence > Issues > Turing's Test (0.33)
Rethinking Weak Vs. Strong AI
Artificial intelligence has a broad range of ways in which it can be applied - from chatbots to predictive analytics, from recognition systems to autonomous vehicles, and many other patterns. However, there is also the big overarching goal of AI: to make a machine intelligent enough that it can handle any general cognitive task in any setting, just like our own human brains. The general AI ecosystem classifies these AI efforts into two major buckets: weak (narrow) AI that is focused on one particular problem or task domain, and strong (general) AI that focuses on building intelligence that can handle any task or problem in any domain. From the perspectives of researchers, the more an AI system approaches the abilities of a human, with all the intelligence, emotion, and broad applicability of knowledge of humans, the "stronger" that AI is. On the other hand the more narrow in scope, specific to a particular application the AI system is, the weaker it is in comparison. But do these terms mean anything?
Is the Chinese Language a Superstition Machine? - Issue 59: Connections
Every year, more than a billion people around the world celebrate Chinese New Year and engage in a subtle linguistic dance with luck. You can think of it as a set of holiday rituals that resemble a courtship. To lure good fortune into their lives, they may decorate their homes and doors with paper cutouts of lucky words or phrases. Those who need a haircut make sure to get one before the New Year, as the word for "hair" (fa) sounds like the word for "prosperity"--and who wants to snip away prosperity, even if it's just a trim? The menu of food served at festive meals often includes fish, because its name (yu) sounds the same as the word for "surplus"; a type of algae known as fat choy because in Cantonese it sounds like "get rich"; and oranges, because in certain regions their name sounds like the word for "luck."
Chinese Room Argument Internet Encyclopedia of Philosophy
The Chinese room argument is a thought experiment of John Searle (1980a) and associated (1984) derivation. It is one of the best known and widely credited counters to claims of artificial intelligence (AI)---that is, to claims that computers do or at least can (someday might) think. According to Searle's original presentation, the argument is based on two key claims: brains cause minds and syntax doesn't suffice for semantics. Its target is what Searle dubs "strong AI." According to strong AI, Searle says, "the computer is not merely a tool in the study of the mind, rather the appropriately programmed computer really is a mind in the sense that computers given the right programs can be literally said to understand and have other cognitive states" (1980a, p. 417). Searle contrasts strong AI with "weak AI."
- North America > United States (0.04)
- Asia > China (0.04)
Searle's Chinese Room Argument: Entry
Against "strong AI," Searle (1980a) asks you to imagine yourself a monolingual English speaker "locked in a room, and given a large batch of Chinese writing" plus "a second batch of Chinese script" and "a set of rules" in English "for correlating the second batch with the first batch." The rules "correlate one set of formal symbols with another set of formal symbols"; "formal" (or "syntactic") meaning you "can identify the symbols entirely by their shapes." A third batch of Chinese symbols and more instructions in English enable you "to correlate elements of this third batch with elements of the first two batches" and instruct you, thereby, "to give back certain sorts of Chinese symbols with certain sorts of shapes in response." Those giving you the symbols "call the first batch'a script' [a data structure with natural language processing applications], "they call the second batch'a story', and they call the third batch'questions'; the symbols you give back "they call . . . Nevertheless, you "get so good at following the instructions" that "from the point of view of someone outside the room" your responses are "absolutely indistinguishable from those of Chinese speakers." Just by looking at your answers, nobody can tell you "don't speak a word of Chinese." Producing answers "by manipulating uninterpreted formal symbols," it seems "[a]s far as the Chinese is concerned," you "simply behave like a computer"; specifically, like a computer running Schank and Abelson's (1977) "Script Applier Mechanism" story understanding program (SAM), which Searle's takes for his example. But in imagining himself to be the person in the room, Searle thinks it's "quite obvious . . .
Is the Chinese Language a Superstition Machine? - Issue 44: Luck
Every year, more than a billion people around the world celebrate Chinese New Year and engage in a subtle linguistic dance with luck. You can think of it as a set of holiday rituals that resemble a courtship. To lure good fortune into their lives, they may decorate their homes and doors with paper cutouts of lucky words or phrases. Those who need a haircut make sure to get one before the New Year, as the word for "hair" (fa) sounds like the word for "prosperity"--and who wants to snip away prosperity, even if it's just a trim? The menu of food served at festive meals often includes fish, because its name (yu) sounds the same as the word for "surplus"; a type of algae known as fat choy because in Cantonese it sounds like "get rich"; and oranges, because in certain regions their name sounds like the word for "luck."
- North America > Canada > Alberta > Census Division No. 6 > Calgary Metropolitan Region > Calgary (0.04)
- Europe > United Kingdom (0.04)