Sintesis pertuturan

Sintesis pertuturan (speech synthesis) adalah penghasilan pertuturan manusia tanpa mengggunakan suara manusia secara langsung.
Secara umum, pensintesis pertuturan (speech synthesizer) adalah perisian atau perkakasan yang mampu menghasilkan "ujaran buatan" (artificial speech).
Sistem ujaran buatan "sintesis pertuturan", yang sering dipanggil sistem teks-ke-pertuturan (text-to-speech, TTS), merujuk kepada keupayaannya untuk menukar teks kepada pertuturan. Bagaimanapun, terdapat sistem yang hanya menghasilkan wakil simbol linguistik seperti transkripsi fonetik kepada pertuturan.

Teknologi-teknologi Buatan

Terdapat dua tekologi utama yang digunaka bagi menghasilkan bentuk gelombang pertuturan buatan: sintetik jeraitan dan sintesis forman

Sintesis forman

Sintesis forman tidak menggunakan apa-apa sampel pertuturan manusia pada waktu jalan. Sebaliknya, Instead, the output synthesized speech is created using an acoustic model. Parameter-parameter seperti tahap-tahap frekuensi asas, penyuaraan dan bunyi diubahkan mengikut masa bagi menghasilkan sebuah gelombang ijaran buatan.  Kaedah ini kadangkala disebut "sintesis berlandaskan aturan" (Rule-based synthesis) tetapi ada yang menyatakan oleh sebab banyak sistem jeraitan (concatenative system) menggunakan komponen berlandaskan aturan buat beberpa bahagian sistem, seperti bahagian depan, istilah ini tidak berapa tepat.
Banyak sistem yang berasaskan teknologi sistem forman menjana pertuturan yang berbunyi bautan dan mirip pertuturan robot; justeru outputnya tidak mungkin akan dianggap sebagai pertuturan seorang manusia.  Walau bagaimanapun, keaslian maksimum bukan selalunya matlamat sistem sintesis pertuturan, dan sistem-sistem memiliki beberapa kelebihan berbanding dengan sistem jeraitan.
Pertuturan hasil sintesis forman dapat didengar dan difahami, mahupun pada kelajuan tinggi, dan mengelak daripada kekacauan akustik yang sering terjadi pada sistem jeraitan. Pertuturan buatan yang laju sering digunakan oleh orang yang kurang upaya kelihatan untuk memandu arah komputer dengan bantuan pembaca skrin. Kedua, pensintesis forman lazimnya merupakan perisian yang lebih kecil daripada sistem penjeraitan oleh sebab sistem forman tidak memiliki pangkalan data sampel pertuturan.  Oleh sebab itu, perisian-perisian ini dapat digunakan dalam pengkomputan terbenam yang mempunyai kuasa pemproses serta ingatan yang terhad. Akhir sekali, sistem-sistem berdasarkan forman memiliki kawalan terhadap semua aspek perturan yang dihasilkan dan dengan itu sebilangan besar prosodi atau intonasi dapat dihasilkan, sekaligus bukan sahaj dapat menggambarkan soalan dan kenyataan, malah juga pelbagai emosi dan nada suara.

Text-to-phoneme challenges

Speech synthesis systems use two basic approaches to determine the pronunciation of a word based on its spelling, a process which is often called text-to-phoneme or grapheme-to-phoneme conversion, as phoneme is the term used by linguists to describe distinctive sounds in a language. 
The simplest approach to text-to-phoneme conversion is the dictionary-based approach. In this approach, a large dictionary containing all the words of a language and their correct pronunciation is stored by the program. Determining the correct pronunciation of each word is a matter of looking up each word in the dictionary and replacing the spelling with the pronunciation specified in the dictionary. 
The other approach used for text-to-phoneme conversion is the rule-based approach. In this approach, rules for the pronunciations of words are applied to words to work out their pronunciations based on their spellings. This is similar to the "sounding out" approach to learning reading. 
Each approach has advantages and drawbacks. The dictionary-based approach has the advantages of being quick and accurate, but it completely fails if it is given a word which is not in its dictionary, and as dictionary size grows, so too does the memory space requirements of the synthesis system. On the other hand, the rule-based approach works on any input, but the complexity of the rules grows substantially as it takes into account irregular spellings or pronunciations. As a result, nearly all speech synthesis systems use a combination of both approaches. 
Some languages, like Spanish, have a very regular writing system, and the prediction of the pronunciation of words based on the spelling works correctly in nearly all instances. Speech synthesis systems for languages like this often use the rule-based approach as the core approach for text-to-phoneme conversion, resorting to dictionaries only for those few words, like foreign names and borrowings, whose pronunciation is not obvious from the spelling. On the other hand, speech synthesis for languages like English, which have extremely irregular spelling systems, often rely mostly on dictionaries and use rule-based approaches only for unusual words or names that aren't in the dictionary.

Speech synthesis markup languages

A number of markup languages for rendition of text as speech in an XML compliant format, have been established, most recently the SSML proposed by the W3C (still in draft status at the time of this writing). Older speech synthesis markup languages include SABLE and JSML. Although each of these was proposed as a new standard, still none of them has been widely adopted.
A subset of the Cascading Style Sheets 2 specification includes Aural Cascading Style Sheets.
Speech synthesis markup languages should be distinguished from dialogue markup languages such as VoiceXML, which includes, in addition to text-to-speech markup, tags related to speech recognition, dialogue management and touchtone dialing.