The speaker is experienced in building synthetic voices.

In the 1930s developed the , which automatically analyzed speech into its fundamental tones and resonances. From his work on the vocoder, developed a keyboard-operated voice-synthesizer called (Voice Demonstrator), which he exhibited at the .

For a large range of Festival synthesis examples see the at CMU.

Scottish English speakers will probably find synthesizers based on this voice strange.

[] CMU_ARCTIC speech synthesis databases, available at .

Examples of non-real-time but highly accurate intonation control in formant synthesis include the work done in the late 1970s for the toy Speak & Spell, and in the early 1980s machines and in many arcade games using the . Creating proper intonation for these projects was painstaking, and the results have yet to be matched by real-time text-to-speech interfaces.

CMU Arctic Databases for Speech Synthesis - CiteSeerX

Until recently, articulatory synthesis models have not been incorporated into commercial speech synthesis systems. A notable exception is the -based system originally developed and marketed by Trillium Sound Research, a spin-off company of the , where much of the original research was conducted. Following the demise of the various incarnations of NeXT (started by in the late 1980s and merged with Apple Computer in 1997), the Trillium software was published under the GNU General Public License, with work continuing as . The system, first marketed in 1994, provides full articulatory-based text-to-speech conversion using a waveguide or transmission-line analog of the human oral and nasal tracts controlled by Carré's "distinctive region model".

Data-driven Phrasing for Speech Synthesis in Low-Resource Languages, ICASSP 2012 Kyoto, Japan.

DATA CMU_ARCTIC speech synthesis databases;

... the English triphone models using these data. 7. Adapt the English full context models using these transforms. 3. EXPERIMENTS 3.1. Experimental setups Data taken from the CMU-ARCTIC English database =-=[16]-=- – about 1 hour of speech data from each of 4 males (awb, bdl, rms, jmk) and 1 female (clb) – was used to train the English Average Voice model The Chinese speech database from the Blizzard Challenge ...

(CMU ARCTIC speech synthesis databases, ..

...y describe the unit search mechanism after that. We then describe the way we generate the target phone sequence from input using a wFST. We finally describe the implementation with CMU Arctic corpora =-=[5]-=- for Blizzard Challenge evaluation, followed by discussions. 2. Probabilistic approach to unit selection In a speech synthesis framework where units are selected from the corpus, we are given some inp...

Speech Synthesis under resource-scarce conditionsSLTU 2010, Penang, Malaysia, 2010.

CMU ARCTIC Databases for Speech Synthesis:

...s was found to produce the smallest error, it was chosen as the baseline approach. The number of components in the source GMM of PLS was 8. A. Acoustic data The publicly available CMU Arctic database =-=[30]-=- sampled at 16 kHz was used for evaluation. We conducted tests for four speaker pairs: male-to-male (M-M), male-to-female (MF), female-to-male (F-M) and female-to-female (F-F). The analysis-synthesis ...

Black, "The CMU Arctic speech databases," in Fifth ISCA Workshop on Speech Synthesis, pp.

18/07/2010 · CMU ARCTIC databases for speech synthesis

This work describes a singing voice synthesis system which uses a MusicXML based music score editor as the front-end interface for entry of the notes and lyrics to be synthesized and a hidden Markov model based text to speech synthesis system as the back-end synthesizer.

(2004)The CMU Arctic speech databasespp 223-224,5th ISCA Speech Synthesis Workshop, Pittsburgh, PA.

CMU ARCTIC databases for speech synthesis.

The HMM-training is done using the HMM-based speech synthesis system HTS [4] (version 2.1) and an English speech database CMU ARCTIC (speaker slt) available in [5]. Here, postfiltering was used instead of global variance.