Phrasebook
to need – to want to » to need – to want to
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EN
English (UK)
- ar Arabic nl Dutch de German EN English (US) en English (UK) es Spanish fr French ja Japanese pt Portuguese (PT) PT Portuguese (BR) zh Chinese (Simplified) ad Adyghe af Afrikaans am Amharic be Belarusian bg Bulgarian
- bn Bengali bs Bosnian ca Catalan cs Czech da Danish el Greek eo Esperanto et Estonian fa Persian fi Finnish he Hebrew hi Hindi hr Croatian hu Hungarian id Indonesian it Italian
- ka Georgian kn Kannada ko Korean ku Kurdish (Kurmanji) lt Lithuanian lv Latvian mk Macedonian mr Marathi no Norwegian pa Punjabi pl Polish ro Romanian ru Russian sk Slovak sl Slovene sq Albanian
- sr Serbian sv Swedish ta Tamil te Telugu th Thai ti Tigrinya tl Tagalog tr Turkish uk Ukrainian ur Urdu vi Vietnamese
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KY
Kyrgyz
- ar Arabic nl Dutch de German EN English (US) es Spanish fr French ja Japanese pt Portuguese (PT) PT Portuguese (BR) zh Chinese (Simplified) ad Adyghe af Afrikaans am Amharic be Belarusian bg Bulgarian bn Bengali
- bs Bosnian ca Catalan cs Czech da Danish el Greek eo Esperanto et Estonian fa Persian fi Finnish he Hebrew hi Hindi hr Croatian hu Hungarian id Indonesian it Italian ka Georgian
- kn Kannada ko Korean ku Kurdish (Kurmanji) ky Kyrgyz lt Lithuanian lv Latvian mk Macedonian mr Marathi no Norwegian pa Punjabi pl Polish ro Romanian ru Russian sk Slovak sl Slovene sq Albanian
- sr Serbian sv Swedish ta Tamil te Telugu th Thai ti Tigrinya tl Tagalog tr Turkish uk Ukrainian ur Urdu vi Vietnamese
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Lessons
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001 - People 002 - Family Members 003 - Getting to know others 004 - At school 005 - Countries and Languages 006 - Reading and writing 007 - Numbers 008 - The time 009 - Days of the week 010 - Yesterday – today – tomorrow 011 - Months 012 - Beverages 013 - Activities 014 - Colors 015 - Fruits and food 016 - Seasons and Weather 017 - Around the house 018 - House cleaning 019 - In the kitchen 020 - Small Talk 1 021 - Small Talk 2 022 - Small Talk 3 023 - Learning foreign languages 024 - Appointment 025 - In the city026 - In nature 027 - In the hotel – Arrival 028 - In the hotel – Complaints 029 - At the restaurant 1 030 - At the restaurant 2 031 - At the restaurant 3 032 - At the restaurant 4 033 - At the train station 034 - On the train 035 - At the airport 036 - Public transportation 037 - En route 038 - In the taxi 039 - Car breakdown 040 - Asking for directions 041 - Where is ... ? 042 - City tour 043 - At the zoo 044 - Going out in the evening 045 - At the cinema 046 - In the discotheque 047 - Preparing a trip 048 - Vacation activities 049 - Sports 050 - In the swimming pool051 - Running errands 052 - In the department store 053 - Shops 054 - Shopping 055 - Working 056 - Feelings 057 - At the doctor 058 - Parts of the body 059 - At the post office 060 - At the bank 061 - Ordinal numbers 062 - Asking questions 1 063 - Asking questions 2 064 - Negation 1 065 - Negation 2 066 - Possessive pronouns 1 067 - Possessive pronouns 2 068 - big – small 069 - to need – to want to 070 - to like something 071 - to want something 072 - to have to do something / must 073 - to be allowed to 074 - asking for something 075 - giving reasons076 - giving reasons 2 077 - giving reasons 3 078 - Adjectives 1 079 - Adjectives 2 080 - Adjectives 3 081 - Past tense 1 082 - Past tense 2 083 - Past tense 3 084 - Past tense 4 085 - Questions – Past tense 1 086 - Questions – Past tense 2 087 - Past tense of modal verbs 1 088 - Past tense of modal verbs 2 089 - Imperative 1 090 - Imperative 2 091 - Subordinate clauses: that 1 092 - Subordinate clauses: that 2 093 - Subordinate clauses: if 094 - Conjunctions 1 095 - Conjunctions 2 096 - Conjunctions 3 097 - Conjunctions 098 - Double connectors 099 - Genitive 100 - Adverbs
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69 [sixty-nine]
to need – to want to
69 [алтымыш тогуз]
69 [алтымыш тогуз]
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Machine Translations
A person who wants to have texts translated has to pay a lot of money. Professional interpreters or translators are expensive. Despite this, it is becoming increasingly important to understand other languages. Computer scientists and computer linguists want to solve this problem. They have been working for some time now on the development of translation tools. Today, there are many different programs. But the quality of machine translations is typically not good. However, the programmers aren't at fault for that! Languages are very complex structures. Computers, on the other hand, are based on simple mathematical principles. Therefore, they can't always process languages correctly. A translation program must learn a language completely. In order for that to happen, experts have to teach it thousands of words and rules. That is practically impossible. It's easier to have a computer crunch numbers. It's good at that! A computer can calculate which combinations are common. It recognizes, for example, which words are often next to each other. For that, it has to be given texts in various languages. This way it learns what is typical for certain languages. This statistical method will improve automatic translations. However, computers cannot replace humans. No machine can imitate a human brain when it comes to language. So translators and interpreters will have work for a long time to come! In the future, simple texts could certainly be translated by computers. Songs, poetry and literature, on the other hand, need a living element. They thrive on the human feeling for language. And it's good that way…
