Ditech Networks is launching software for cell phone companies today that will allow them to build Bluetooth headsets and hands-free cell phone car kits with much better call quality.

The company says it has created mathematical formulas, or algorithms, that make it much easier to remove the noise and sharpen quality in a cell phone call for both the person with the Bluetooth headset and the person at the other end of the line.

Ditech’s rivals include Aliph, maker of the Jawbone Bluethooth headset, and audio chip maker Audience.  Aliph custom designs a complete system for its Jawbone head set, which sells for $129. The Jawbone eliminates background noise and enhances the quality of the voice transmitted by monitoring the movement’s of a person’s jawbone. Audience, meanwhile, sells chips that allow for better noise reduction and call quality. The company says it can do so because it models its designs on the way the human ear works.

But Ken Croley, senior director of corporate marketing at Ditech in Mountain View, Calif., says that it takes much less processing power to run Ditech’s VQABlue software on a Bluetooth head set than it does to run on Audience hardware. While Audience’s processors operate at 22 million instructions per second, Croley claims that Ditech’s software can run fine at 6.8 MIPS.

The software could be licensed broadly to customers that already use Ditech’s software for existing phones and headsets. It takes both less memory and processing power, resulting in a phone with less electronic content, lower costs, and better battery life, Croley said.

This launch shows that technology can still trickle down a waterfall. It starts at the high end and moves to the low end. Technology also migrates from special-purpose hardware to software. On a software level, Ditech competes with rivals Acoustic Technologies, Dynamic Hearing, and NFore. Ditech says its solution is better than the rivals because of the combination of high quality, lower cost, and lower battery requirements.

Ditech has put more than 10 years of development into its digital signal processing algorithms, the latest of which are used in the VQABlue software. The software can be used in single-microphone or dual-microphone Bluetooth headsets that sell for $80 to $120. That’s higher cost than the typical low-tech headsets, which typically run as little as $20.

Ditech’s software can run on Bluetooth chip maker CSR’s BlueCore5 multimedia platform chip set. That chip set is widely used in the industry. The software includes noise cancellation, echo control, enhanced voice sharpness, and adaptive listener enhancement. All of that means listeners won’t have to spend as much energy trying to hear the words on a call, Croley said.

Ditech’s customers include Verizon, Sprint/Nextel, Orascom Telecom, AT&T, China Unicom, Global Crossing and West Corporation. Ditech is publicly traded on Nasdaq and was founded in 1997. The company says it has been able to improve the quality of cell phone calls by experimenting with improvements for existing customers. The company has 120 employees.

Aliph has been able to do what a lot of companies haven’t in the wireless headset market: Sell something expensive while the competition is selling cheap stuff.

With its Jawbone wireless cell phone ear piece launched in 2006, the company has so far sold millions of units at a hefty price of $129 in a commodity market where cheap ear pieces sell for $40.

It has done so with a unique audio technology that it had been working on since 1999. The Jawbone Bluetooth headset had features that enabled its user to hear their calls more clearly, even in noisy environments.

Today, the company is launching its second-generation product.

The new Jawbone is smaller and has a sleek-looking design. Aliph chief executive Hosain Rahman said the new headset will have even better noise elimination than the first one and will fit better on most ears. It now has a leather-covered hook for the ear instead of a plastic one and it is 50 percent smaller.

The Jawbone features a patented design where a small plastic nub rests on the cheek of the user. It records the vibrations and movements from the user’s jawbone and uses that data to determine what the person is saying. It then uses an audio processor to filter out background noise. Aliph calls this the Jawbone Noise Assassin, a technology originally developed by the Department of Defense’s DARPA agency for battlefield use. The Jawbone also raises the volume of the headset whenever the user is in a noisy place. The company claims it eliminates 10 times as much noise as rival headsets.

The new Jawbone goes on sale at AT&T stores around the country. Bluetooth headets are expected to top 120 million units sold in 2009, partly because some states such as California will require that drivers use such headsets when using cell phones in a car.

Aliph is based on San Francisco and has been funded by Khosla Ventures and Sequoia Capital. It competes with other audio technology companies such as Audience, which recently raised a $15 million round for its audio processing chips.

The new Jawbone weighs 10 grams, has four hours of talk time on a battery charge, has eight days of standby time, and charges in one hour.

Some very smart people believe machines will take over — directing human affairs — sometime soon, perhaps within the next thirty year.

So much malarkey, you think, until you consider the sorts of technologies being developed lately — which start to replicate human intelligence one step at a time.

There’s Silicon Valley’s Numenta, the company started by Palm founder Jeff Hawkins, which is building a computer system that aims to be think like the human brain. We’ve mentioned the company before, but Dean Takahashi, who starts writing for VentureBeat next week, provides an update about the fascinating company. Numenta’s software copies the human brain’s way of recognizing patterns with hierarchical memory (such as recognizing a dog shape; see image above and explanation here). Some 100 or so developers and eight companies are working to develop the software, and are applying it to several application areas, including visual object recognition and speaker voice identification.

It is the latter area, voice identification, that is seeing significant innovation — in part because of the booming mobile phone industry it serves. At the Mobile World Congress in Barcelona last week, another Silicon Valley company, Audience, emerged saying it has build a chip and software modeled that aims to function like the human ear in order to improve the sound quality of cellphones. It suppresses background noise by mimicking the human ear, which breaks down sounds into recognizable components of speech, and so can thereby ignore other sources of sound. See the New York Times story about the Mountain View, Calif. company.

It was started by Lloyd Watts, a neuroscientist who studied with the physicist Carver Mead of Cal Tech. Paul Allen, a co-founder of Microsoft, along with several venture capital firms, including New Enterprise Associates, have pumped in more than $22 million into the company, we’ve learned.

Forest Baskett, an investor at NEA, told VentureBeat Audience blows away competing technologies. Incumbents include Forte Media, which uses technology that forms a beam in order to track your voice, but which can experience interference if there’s background noise finding its way into the beam. There’s also Softmax, which uses multiple microphones, and assumes it can sort out which voice source to focus on, but which breaks down in busy environments too, such as airports, where you can have five to ten sound sources at any given time. Qualcomm recently bought Softmax.

Yesterday, another voice identification company Solicall, of Israel, emerged saying its sophisticated technology serves Windows Mobile, and also beats existing sound identification technologies. SoliCall’s software focuses on the specific voice of the speaker, using a personalized filter that first learns your voice and afterwards, during any call, passes through only your voice and screens all other voices, noises and sounds. It’s based an algorithm for which the company has filed a patent.

These bite-sized developments, where technology starts to mimicking the human, aren’t doing it the centralized Frankenstein way, but from the edges, one step at a time.