The aim of this article is to urge all concerned stakeholders to take hate seriously. Its novelty lies in the hard evidence and findings collated here. First, it reports on the results of a long-standing study of dozens of fascist and racist websi- tes, documenting what radical members of the White mo- vement are saying but letting readers judge the severity of the statements. In this respect, the article aims to evoke awareness regarding the mind-set, concerns and language of the people who hate. While not all forms of hate speech lead to hate crimes, still there is sufficient evidence to sug- gest that speech can and does inspire crime. It is argued that the Internet attracts those who are prone to adopt hateful messages, and that it prompts people into action. It is by no means the only way to spread ideas and to push people to action, but one should not disregard or dismiss the Inter- net’s significance and importance.
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A purposive sample of 30 hate messages exchanged between January 2013 and May 2013 was chosen for the analysis based on two of the categories used by Umati to monitor hate speech: offensive speech and extremely dangerous speech. The research sampled 15 messages for each category. The researcher purposively sought messages that were extremely inciting either because they either used derogatory remarks, explicitly called members of one community to kill members of another community, explicitly called for one community to forcibly evict members of another community from their land as well as those that were offensive in that they were intended to insult a particular group through stereotypes or sheer abuses. The messages were therefore analysed under the two themes/ categories: offensive speech and extremely dangerous speech. The main aim was to examine how citizens used new media (tweeter and Facebook) to fight out their ethnic wars online unlike in 2007/2008 post election violence where the war was physically on the streets.
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Abstract. The Peace Agreement signed between the Colombian Government and the FARC guerrilla in 2016 allowed this group, now as a political party, to nomi- nate candidates in the parliamentary and presidential elections held in the first half of 2018. This has been strongly criticized by a group of Colombians, who have rejected it in physical and virtual spaces, to the point of forcing the new party to cease its campaign in public spaces. This article tries to reflect these reac- tions in two groups of Facebook, identify the communicative elements used in the interaction and analyze if there is a violent or hate speech, based on a digital ethnographic observation and content analysis. To this end, publications linked to the announcement of the candidacy for the presidency of Rodrigo Londoño 'Timochenko', to the presidency of Colombia, were reviewed in November 2017, which allowed identifying factors that favor the appearance of violent and hate speech, and the lack of interaction and use of communication tools of the digital environment in this type of message. Keywords: Violent speech; Hate speech; Colombian peace process, Facebook interaction.
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lipstick and be who you really are” may not be categorized as some form of hate speech when only read in isolation, however, if this expression is directed towards a boy one may perceive it as an attack to the sexuality or gender identity of the boy being addressed. The basis of this model is to encode concepts that are connected by relations and stereotypes to form assertions, such as “a skirt is a form of female attire” or “lipstick is used by girls”. This knowledge base allows computing the similarity of concepts of common knowledge with concepts expressed in user comments. Obviously, this approach only works for a very confined subtype of hate speech (i.e, anti-LGBT bullying). It could also be used for other types of hate speech but it would require domain specific assertions to be included and this would require a lot of manual work.
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Although it is the most common tool, re- searchers have deepened in the validity of surveys as a method to measure attitudes towards migrants and refugees due to the aforementioned social desirability bias (Cea D’Ancona, 2009; Díez Nicolás, 2009). Also, the studies based on social media are gain- ing relevance, as it is in them where a great part of the public discourse of contem- porary societies takes place. As Schäfer and Schadauer (2019) observed, fake news and disinformation spread online are of- ten behind contents that promote rejection against migrants and refugees. And, given that the phenomenon of fake news cannot be separated from social media (Bakir and McStay, 2018), the study of these is of par- ticular interest. That is why Twitter has be- come one of the platforms that most pop- ularity has gained for scientific researches. Focused in the attitudes towards migrants and refugees, Chaudhrey (2015) has proven the capacity of this platform to track online racism. More recent studies have tried to stablish correlations between hate speech in social media and cases of violence, like Müller and Schwarz (2018), who studied the connection between social media and hate crimes using data from Facebook and Twitter. In general terms, using digital tools like Twitter in order to download and proc- ess great volumes of data and analyze at- titudes towards migrants and refugees is gaining relevant, as shown by a study with 862,999 tweets of Gallego et al. (2017), which includes a gender perspective to the study of the representation of refugees. Re- bollo and Gualda (2017) conducted a simi- lar study with a sample of 151,294 tweets in Spanish and, despite having different goals, this method was also used by Gualda et al. (2015). The present work also follows the
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81. El asunto Murat Vural es consecuencia de la reiteración del acto de pintar la estatua de Atatürk, quien fuera el primer presidente de la República de Turquía. En lo que fue una muestra de manifes- tación y protesta política, de forma unánime “[t]he Court considers that the same can be said for any individual who may wish to convey his or her opinion by using non-verbal and symbolic means of expression, and it thus rejects the Government’s argument that ‘[a]lthough the applicant had the right to express and disseminate his thoughts and opinions through speech, writing, pictures and other mediums without recourse to violence, he had chosen not to do so’”. Vid. STEDH, de 21 de enero de 2015, Murat Vural vs. Turkey, párr. 53.
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Video information was also recorded for every utterance. The main purpose of this capture is allowing research on emotion detection using visual information, face tracking studies and the possibility of study specific head, body or arms behaviour that could be related to features such as intensity level in the recorded speech signals or give relevant information of each emotion played. Also, audio-visual sensor fusion for emotion identification and even affective speech recognition are devised as potential applications of this corpus.
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As already pointed out in the introduction, this strategy does not function as indirect speech acts designed as a face-saving measure, but as a way of maintaining the activists’ cooperative attitude in this debate. In addition, the analysis of other discursive features reveals that the illocutionary force of her accusation is not reduced by this affiliative strategy. These discursive features are the following: a) the lexical terms “development projects” in (57)-(58), and “voluntary social action” in (65) work as contextualization cues that reinforce the company’s negative behaviour (they activate an assistance model of development); and b) various deontic structures activate the opposite frame, the one based on the compliance with rights, which is proposed to the company as an obligation: debe ser ‘[it] should be’ in (64), debería ser aplicada ‘[it] should be applied’ in (73), and deben ser ‘[they] must represent’ in (93).
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Imagery, as the initial category of artistic discourse, is based on spontaneous creativity of living colloquial speech, which is understood as a non-standard type of nomination or predication. In both cases, the appearance of an image is associated with the transforming action of an author or a speaker, his desire (sometimes subconscious one) not to use, but to “influence the language” (Budagov, 1979). This deviation from cliches and model conventions accepted in communication is aimed most often at the information flow or narrative sequence revitalization with a “spectacular” effect – a bright figurative “inlay” (Zemskaya et al, 1981). “shaking automatism” of perception (Norman, 2011). and enhancing the expressive aspect of an utterance. From a pragmatic point of view, speech expressiveness increase invariably reduces its information content, which, in turn, determines the functional limitation of figurative means (Vinogradov, 1980). However, this situation, traditional for stylistics, has recently undergone significant changes under the pressure of communication “image” nature in the public sphere (Adonina et al, 2018: Polyanskaya et al, 2018: Rumyantseva et al, 2018). The illocutionary power of a speech act and the perlocution that was not obvious in it is appreciated much higher than information accuracy. Imagery allows not only to draw the attention of the audience to certain (sometimes secondary, non-essential) aspects of a problem, but also to emphasize a speaker’s individuality, including the degree of his creativity. Thus, the demand for imaginative means in modern communication technologies determines the relevance of research aimed at observing and clarifying the mechanisms of linguistic influence, also by the means of creative deviations (Nikolina, 2013).
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Examining influential factors by means of manipulation is a commonly used method. The focus of such experiments lies primarily not in examining the components and their rela- tionships per se, but concentrates on detecting variables and constants in order to obtain a projection model of speech qua- lity assessment that is supported by data. Using a model to describe what has happened is necessary because natural spe- ech quality assessment processes are very complex. Mode- lling is possible because, in spite of everything, the processes lead to similar results when similar circumstances are present, and several listeners are questioned. Speech quality measu- rements drive at functional invariances. The listeners’ beha- viour cannot be put down to arbitrariness, but it is strategic and subject to a certain systematology. The prerequisite of high quality speech quality measurements is to analyse this systematology by means of a structuralistic approach and to obtain a simplified simulation, i.e. a projection model, which agrees with the findings. The principle used for the modelling assumes that the event of a natural speech quality assessment is a structured whole that can be described as a system. In this system, the significance of the components that constitute the whole are characterized by a holistic structure. This structure is an abstract model which is not subject to variations.
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The vocal tract resonances shown in Figure 3 (right) as bright bands pinpointing formant positions will enhance the energy of the nearby harmonics. Unvoiced speech shows also strong dominant bands which can not be considered formants in the strict sense, but that are due also to specific resonances when turbulence is produced at the back of the oral cavity, as is the case of / χ a / between 1.35-1.50 sec. This means that speech is perceived as sequences of harmonic series which may be preceded or followed by consonant-specific noisy bursts, coloured by the resonances of the vocal tract with characteristic onsets and trails, therefore formants will play a dominant role in speech perception.
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AAC: Advanced audio coding; ASR: Automatic speech recognition; ATWV: Actual term-weighted value; BUT: Brno University of Technology; DET: Detection error tradeoff; DNN: Deep neural network; DTW: Dynamic time warping; FA: False alarm; GMM: Gaussian mixture model; HMM: Hidden Markov model; HNR: Harmonics-to-noise ratio; IARPA: Intelligence advanced research projects activity; INL: In-language; INV: In-vocabulary; KWS: Keyword spotting; LM: Language model; LVCSR: Large vocabulary continuous speech recognition; MED: Minimum edit distance; MFCC: Mel-frequency cepstral coefficient; MOS: Mean opinion score; MPEG: Moving picture experts group; MTWV: Maximum term-weighted value; NIST: National institute of standards and technology; NS-DTW: Non-segmental dynamic time warping; OOL: Out-of-language; OOV: Out-of-vocabulary; PCM: Pulse code modulation; QbE STD: Query-by-Example Spoken Term Detection; QUESST: Query-by-Example Search on Speech Task; RTVE: Radio Televisión Española; S-DTW: Subsequence DTW; sBNF: Stacked bottleneck feature; SDR: Spoken document retrieval; SIG-IL: Special interest group on iberian languages; SoS: Search on speech; STD: Spoken term detection; SWS: Spoken web search; TV: Television; TWV: Term-weighted value; VAD: Voice activity detection; WFST: Weighted finite state transducer
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The m(F) values are obtained for each modulation frequency F between 0.63 Hz and 12 Hz in 1/3 octave steps (14 in total). This range covers the speech modulations. The carrier noise signal is octave band filtered between 125 Hz and 8 kHz. In this way there are 7 ×14=98 m(F) values. These modulation reduction factors are converted into apparent signal/noise ratios and are properly weighted and averaged to calculate the STI index . Fig.1 shows a possible scheme to calculate MTF. This method is implemented, for example, in the free PC-software STI ver.-2.0 from Lexington School for the Deaf , where the stimulus signal consists of a band limited white carrier noise modulated by low frequency sine waves. Each measure takes about 2 minutes to apply all the modulation frequencies to the test system successively.
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The five features are the most discriminative MFCCs (C1, C2 and C3), obtained from a previous study which is developed and explained latter in this section (Table I), normalized log energy (c0n) and delta log energy (dc0) calculated at every frame. In this work, every frame includes audio samples during 24 ms with a 50% overlapping between consecutive frames. The GenCeps module computes MFCCs from a 12 Mel filter bank with pre-emphasis. If this specific feature extraction (MFCCs) is also used for speech recognition, front-end calculation will not increase the processing time
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Ting and Chiders (1990) described a recursive least-squares algorithm with a variable FF, and introduced for speech signal analysis. The variable FF was a function of the state changes of the estimator. Pahalawatha et al (1990) used to variable FF in the recursive least squares algorithm. Bittanti and Campi (1994 a ) worked a constant FF to parameter tracking with recursive least square
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In spoken language we are not only communicating a message, we are also provid- ing information about the contextual circumstances in which the message occurs. This contextual information can reveal us many things, such as the gender of the speaker, his age, his identity or even the emotion expressed by him, among many other things; but above all, it can give us information on the subject on which the speaker is talking about. If we could incorporate this contextual information into the speech recognition technology, then we could adapt the recognition to the context of the speech that is being decoded, enhancing thus the performance of the recognizer. Therefore, the hy- pothesis we are addressing in this work is based on the possibility of identifying the semantic elements of the spoken language that give us information about the context, and particularly, about the topic. These elements could be extracted by means of Infor- mation Retrieval and Machine Learning techniques, and would allow us, within a con- textualization framework, to adapt the language models used by a speech recognizer to the contextual conditions of the speech. This contextual adaptation could improve the recognition performance when compared to the results achieved by unadapted systems. In accordance to our research hypothesis, the primary objective of this Thesis is to propose and evaluate a framework of topic-motivated contextualization based on the dynamic and non-supervised adaptation of language models for the enhance- ment of an automatic speech recognition system.
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hace alrededor de 15 años, la música electrónica comenzó a emerger en nuestro país, allí Dicho lugar se encontraba ubicado en la zona rosa de la ciudad de Bogotá y poco a poco comenzó a ver el negocio de una discoteca como algo más, se interesó por traer al país artistas internacionales a su discoteca teniendo una gran aceptación por parte de sus clientes, al ver la oportunidad de entretenimiento como un negocio más grande decidió realizar eventos de talla mayor con la misma acogida que tuvo en un principio en su bar, hoy en día hace eventos de talla mundial llenando espacios de hasta 15.000 personas para un solo artista, HATE LOVE, se caracteriza por traer lo más exclusivo y selecto de los exponentes actuales de los géneros alternativos y se encarga solo con su buen nombre de llenar estos espacios, detrás de esto también se concentra todo una serie de alternativas publicitarias para sus clientes pautantes quienes indirectamente son quienes terminan pagando todo el artista con su pauta y patrocinio, HATE LOVE se encarga de realizar el evento bajo su propia marca generando utilidades muy grandes en una sola noche.
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,U[YLLZ[LS[PTV[PWVKLLZ[YH[LNPHZKLZ[HJHUSHZJHTWH|HZX\LPUJS\`LUHJ[P]PKHKLZKP]LY sas con el objetivo de atacar los prejuicios y la intolerancia como raíz del problema del dis- J\YZVKLSVKPV`X\LW\LKLUJH[LNVYPaHYZLLU[YLZ[PWVZ!KLZLUZPIPSPaHJP}UHÄYTH[P]HZV YLZ[YPJ[P]HZ;P[SL`2LLU`-SKP4LUJP}ULZWLJPHSTLYLJLSHJHTWH|HNo Hate, pro- movida por el Consejo de Europa, por la repercusión alcanzada y por ser una campaña inte- NYHSX\LPUJS\`L\UHHTWSPH]HYPLKHKKLLZ[YH[LNPHZLU[YLSHZX\LKLZ[HJHLSKLZHYYVSSVKL contranarrativas. La contraargumentación a través de un discurso alternativo y deslegitima- KVYKLSKPZJ\YZVKLSVKPVLZ\UHKLSHZLZ[YH[LNPHZLUSHZX\LZLOHUKLWVZP[HKVTH`VYLZ expectativas por parte de las instituciones públicas y de las propias redes sociales.
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Although our knowledge of the basic concepts of speech privacy are now over 50 years old, there are still some unresolved issues. The special case of speech pri- vacy in open-plan offices has been most thoroughly in- vestigated and it is possible to specify achievable de- sign goals that will help to improve the work environ- ment for occupants of open-plan offices. For enclosed offices and meeting rooms, we can give procedures and design goals that can provide practical solutions to achieving an adequate degree of speech security. How- ever, there are many details remaining to be explored to better understand how we can help to improve speech communication or speech privacy for all listeners in all types of listening environments. For example, more work is required to evaluate the use of measures that combine the effects of signal-to-noise ratios and room acoustics effects such as the Speech Transmission Index and Useful-to-Detrimental sound ratios. They may need to be expanded beyond their essentially monaural cur- rent forms to more completely explain conditions in room for speech.
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This paper discusses the ClassTalk system for modeling, predicting and visualizing speech in noise in classrooms. Modeling involves defining the classroom geometry, sources, sound- absorbing features and receiver positions. Empirical models, used to predict speech and noise levels, and reverberation times, are described. Surface absorption coefficient contributions are assigned based on previous work. Male or female speech sources, and overhead-, slide- or LCD-projector, or ventilation-outlet, noise sources can have four output levels; values are assigned based on ranges of values found from published data and on measurements. ClassTalk visualizes the floor-plan, speech- and noise-source positions, and the receiver position. The user can ‘walk through’ the room at will. In real time, five quantities - background- noise level, speech level, signal-to-noise level difference, Speech Transmission Index and speech intelligibility - are predicted and displayed, along with occupied and unoccupied reverberation times. An example of a large classroom before and after treatment is presented. The future development of improved prediction models and of the sound module, which will auralize speech in noise with reverberation, is discussed.
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